Friday, August 15, 2025

 

New monoclonal antibody targets deadly sepsis




University of Virginia Health System





Scientists at the University of Virginia School of Medicine and the University of Michigan have developed a monoclonal antibody to stop sepsis, a deadly full-body infection. The antibody also has the potential to treat a broad array of other inflammatory conditions, including autoimmune disorders, their research indicates.

In initial testing in lab mice, the antibody proved versatile and showed “transformative potential for combatting life-threatening inflammatory diseases,” the researchers report in a new scientific paper. Potential applications could include deadly acute respiratory distress syndrome (ARDS), which rose to public attention during the COVID-19 pandemic, as well as ischemia-reperfusion injury, which is tissue damage caused when blood flow is cut off and restored. (Ischemia-reperfusion injury is a major problem for organ transplantation.)

The researchers say their work has also shed light on the molecular causes of sepsis and has the potential to produce an important tool for diagnosing the condition and monitoring patients.

“This is the kind of breakthrough that can change the standard of care,” said Jianjie Ma, PhD, of UVA’s Department of Surgery and UVA Cancer Center. “By combining complementary expertise in basic science, innovation and translational medicine, and by working closely with our industry partners, we’ve developed a first-in-class antibody with the potential to save countless lives from sepsis and other severe inflammatory diseases.”

Stopping Sepsis

Sepsis strikes up to 50 million people worldwide every year, killing approximately 11 million. It is a leading cause of death in U.S. hospitals, and the risk of death increases every hour it goes untreated. It is caused when the body’s immune response spirals out of control in response to an infection, potentially leading to organ failure and death. Even with aggressive treatment, up to 40% of patients who reach the most severe stage of sepsis still die.

Ma and his collaborators’ new antibody, they hope, could become the first treatment that directly targets the underlying immune system dysregulation responsible for sepsis. It seeks to prevent the “cytokine storms” that made headlines in the pandemic, shutting down the body’s hyperactive immune response before organ damage can occur.

Further, early testing suggests the antibody can do so without the unwanted side effects of existing sepsis treatments, such as unintended suppression of the immune system. In the initial studies, the antibody was able to stop inflammatory cytokines and restore the function of immune cells called macrophages, all while protecting against sepsis-induced lung injury, the scientists report in their new paper.

In addition to the antibody’s potential therapeutic applications, the scientists say the tools they are using to produce it may be useful for detecting and monitoring sepsis. Their platform, called PEdELISA, can quantify six cytokines from a single drop of plasma within two hours.

“Our humanized antibody has shown both safety and effectiveness in blocking the cytokine storm and restoring healthy immune function,” said Yongqing Li, MD, PhD, of the University of Michigan Medical School. “Beyond treating acute infections, it has the potential to address a spectrum of diseases caused by faulty immune regulation, including autoimmune disorders, cancer and diabetes.”

The researchers have received $800,000 from Virginia Catalyst to launch a clinical trial of the antibody at UVA Health and Virginia Commonwealth University. The antibody has been extensively engineered for clinical application and presents significant translational potential, particularly when coupled with the PEdELISA diagnostic platform..

“Integrating PEdELISA with this first-in-class antibody therapy enables a comprehensive approach to sepsis management, allowing not only earlier and more accurate diagnosis but also continuous, near real-time monitoring of the patient’s immune status throughout treatment. This integration could facilitate timely therapeutic adjustments, prevent disease progression and ultimately increase the likelihood of achieving complete resolution,” industry partner Guidong Zhu said.

Better Understanding Sepsis

As they have developed their antibody, the scientists have made important discoveries about the underlying molecular mechanisms responsible for sepsis. The researchers identified changes that take place in macrophages that spur harmful “feedback loops” that drive the body’s uncontrolled inflammatory response. The researchers’ new antibody, they found, interrupts those changes.

Ultimately, Ma and his collaborators hope their sepsis work will help overcome one of the great challenges in medicine. Finding those types of lifesaving, game-changing solutions is exactly the mission of UVA’s new Paul and Diane Manning Institute of Biotechnology.

“UVA is proud to be part of this groundbreaking discovery,” said Melina R. Kibbe, MD, dean of UVA’s School of Medicine. “Our leadership is eager to work hand-in-hand with clinicians and industry partners to move this bench discovery into the clinic, where it could make the difference between life and death.”

Findings Published

The researchers have published their findings in the scientific journal Nature Communications. The research team consisted of Wenlu Ouyang, Yuchen Chen, Tao Tan, Yujing Song, Tao Dong, Xin Yu, Kyung Eun Lee, Xinyu Zhou, Zoe Tetz, Sophia Go, Xindi Zeng, Liujiazi Shao, Chao Quan, Ting Zhao, Yuzi Tian, Katsuo Kurabayashi, Hua Jin, Jichun Ma, Jingdong Qin, Brandon Williams, Qingtian Li, Zhu, Hasan B Alam, Kathleen A. Stringer, Yongqing Li and Ma. 

UVA has filed a patent application related to the work. Ma and Li are co-founders of HTIC Inc., a company that develops antibodies to regulate immune systems. Ma was honored in January with the Dean’s Excellence in Faculty Research Award from UVA’s School of Medicine.

The sepsis research was supported by the National Institutes of Health, grants R01HL155116, R01HL157215, R01AG07240, R01EY036243 and R35GM136312, and a Joint-of-Institute grant, U068874.

To keep up with the latest medical research news from UVA, subscribe to the Making of Medicine blog at http://makingofmedicine.virginia.edu.

 

Experience does not guarantee success for hiring CEOs



Study turns spotlight on hiring processes for company heads



University of Mississippi

Hiring CEOs 

image: 

Top: Despite frequent CEO turnover, a new study indicates that company directors aren't always good at hiring CEOs just because they've done it before. In fact, they may even repeat past mistakes, an Ole Miss business researcher says.

view more 

Credit: Graphic by Stefanie Goodwiller/University Marketing and Communications





OXFORD, Miss. – When companies replace their CEOs, the stakes are high. But a new study shows that hiring boards might not be getting better at the process, even with practice. 

Chief executive turnover was at an all-time high in 2024, when more than 2,220 company leads stepped down from their positions. How good are hiring boards at replacing them? And do they get better the more they do it?  

Researchers posed these questions in a recent publication in Strategic Management Journal.  

“Most people improve with practice, but we find that this doesn’t hold true when it comes to directors selecting new CEOs, despite the high stakes,” said Rich Gentry, chair and professor of management at the University of Mississippi. “We found that directors with more past experience in CEO hiring do not tend to select better-performing CEOs.  

“In fact, there's some evidence they may do slightly worse.” 

The researchers included Gentry, Steven Boivie, Carroll and Dorothy Conn Chair in New Ventures Leadership at Texas A&M, Inn Hee Gee, assistant professor in the Division of Management and International Business at the University of Oklahoma, and Scott Graffin, head of the Department of Management at the University of Georgia.  

The team reviewed the hiring processes of CEOs from S&P 1500 firms – a mix of top U.S. companies of all sizes – from 1999 to 2020.  

“Hiring a CEO is very difficult, and it is almost impossible to know in advance who would be the perfect CEO,” Boivie said. “Because of that difficulty, it is easy for boards to overinterpret their prior experiences and to believe they should copy those same patterns. 

“If directors know that they need to avoid overgeneralizing from their prior experiences, then they might make fewer hiring errors.” 

The lead position in any organization often comes with high pressure and high stakes, meaning the decision to hire is an important one, the researchers said.  

“CEOs are asked to manage two different things,” Gentry said. “One is the short-term stock market performance. At the same time, they're asked to keep the company going for the long term.”  

Former film photography giant Kodak, for example, faced harsh criticism after its CEO pushed the company to invest in digital photography – a smart move in the long term. But at the time, analysts criticized the decision for harming short-term profits. Kodak ultimately filed for bankruptcy and restructured, despite being ahead of the curve technologically. 

In contrast, Microsoft’s board saw long-term success after hiring CEO Satya Nadella in 2014. Nadella’s embrace of cloud computing helped revitalize the company and dramatically grow its value while maintaining short-term profits.  

The researchers gauged the performance of CEOs using metrics such as firm performance adjusted for industry norms and company condition at the time of hire. They found that just because a board member has been on the hiring team for a CEO before doesn’t mean they’ve hired a successful one, or that they know what to look for in a leader, Gentry said.  

“That’s superstitious learning – the concept that ‘I’ve done it before; therefore, I probably know what I’m doing,’” he said. “Most humans have this concept of self-efficacy, but when it comes to a rare and complex event like hiring a CEO, it doesn’t always work that way.”  

Most directors face this decision only once or twice in their tenure, making it difficult to build reliable experience, the researchers said.  

“The implication of this study is that relying too heavily on prior hiring experience and overgeneralization can result in less successful hiring,” Gee said. “As Steve noted, if directors acknowledge these limitations and approach each hiring decision with deep contextual understanding, they may be able to avoid decision making errors.” 

To hire better, more successful CEOs, boards need to rely not on previous experience, but on structured evaluation and multiple perspectives while treating each hiring as a unique event.  

“CEO successions are rare, complex and highly context-specific events, making it easy for directors to misattribute what worked before,” Gentry said. “Our findings suggest that boards likely need more systematic support – beyond accumulated experience – when hiring new CEOs.” 

 

Unusual case of rare ovarian tumor mimicking pregnancy with successful treatment outcome



“Our case illustrates the classic features of NGOC, including significant bleeding, markedly elevated β-hCG levels, and a unilateral adnexal mass on imaging”



Impact Journals LLC

A rare case of pure non-gestational ovarian choriocarcinoma: Diagnostic mimicry and management strategies 

image: 

Figure 1. Transabdominal sonography image revealing a well-defined, predominantly solid-cystic lesion (10.2 × 7.8 × 7.8 cm) with vascularized solid components in the right adnexa with areas of hemorrhage.

view more 

Credit: Copyright: © 2025 Kumar et al. This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.






“Our case illustrates the classic features of NGOC, including significant bleeding, markedly elevated β-hCG levels, and a unilateral adnexal mass on imaging.”

BUFFALO, NY — August 14, 2025 — A new case report was published in Volume 12 of Oncoscience on July 28, 2025, titled “A rare case of pure non-gestational ovarian choriocarcinoma: Diagnostic mimicry and management strategies.”

This report, led by Naina Kumar from the All India Institute of Medical Sciences, Bibinagar, details the case of a 36-year-old woman diagnosed with a rare pure form of ovarian cancer called non-gestational ovarian choriocarcinoma (NGOC). This is an extremely rare tumor, affecting less than 0.6% of malignant ovarian germ cell tumors. It usually appears in young women and is difficult to diagnose because it shares symptoms with pregnancy-related conditions, such as vaginal bleeding and high levels of the pregnancy hormone β-hCG. 

Non-gestational ovarian choriocarcinomas (NGOC) are rare, distinct, highly aggressive tumors, primarily affecting young women.”

In this case, the patient had been experiencing abnormal bleeding for several months. A positive pregnancy test and imaging studies led doctors to initially suspect an ectopic pregnancy. Advanced imaging and blood tests revealed a large mass in the right ovary. Surgery was performed to remove it along with the uterus, ovaries, and nearby lymph nodes. Genetic testing of the tumor tissue showed that it contained only maternal DNA, confirming it as non-gestational. This confirmation is important because non-gestational tumors are more aggressive and respond differently to treatment compared to tumors linked to pregnancy.

The patient received a chemotherapy regimen that included Bleomycin, Etoposide, and Cisplatin. After two cycles, her β-hCG levels returned to normal, indicating a complete response to treatment. She remains under regular follow-up with hormone monitoring and imaging scans to evaluate for any recurrence.

This case highlights the challenge of diagnosing pure NGOC, especially when the symptoms closely resemble more common conditions. It also shows how genetic testing and imaging can help guide accurate diagnosis and appropriate treatment. Early detection and timely intervention can lead to favorable outcomes, even in aggressive cancers like NGOC.

As one of the few documented cases of pure NGOC, this report adds valuable knowledge to the limited literature on this rare tumor type. It emphasizes the need for clinicians to consider rare diagnoses when common conditions do not fully explain a patient’s symptoms.

Continue reading: DOI: https://doi.org/10.18632/oncoscience.622

Correspondence to: Naina Kumar – naina.obg@aiimsbibinagar.edu.in

Keywords: cancer, chemotherapy, ectopic pregnancy, germ cell tumor, gestational ovarian choriocarcinoma, non-gestational ovarian choriocarcinoma

Click here to sign up for free Altmetric alerts about this article.

About Oncoscience

Oncoscience is a peer-reviewed, open-access, traditional journal covering the rapidly growing field of cancer research, especially emergent topics not currently covered by other journals. This journal has a special mission: Freeing oncology from publication cost. It is free for the readers and the authors.

Oncoscience is indexed and archived by PubMed, PubMed Central, Scopus, META (Chan Zuckerberg Initiative) (2018-2022), and Dimensions (Digital Science).

To learn more about Oncoscience, visit Oncoscience.us and connect with us on social media:

Click here to subscribe to Oncoscience publication updates.

For media inquiries, please contact media@impactjournals.com.

Ensemble AI unlocks hidden tree crown structures in dense forests





Nanjing Agricultural University The Academy of Science





The method not only overcomes limitations of traditional LiDAR scanning but also enables the extraction of other hard-to-measure crown parameters, promising to advance forest management, breeding, and ecological modeling.

Tree crown architecture reflects a tree’s competitive environment and influences growth, productivity, and photosynthesis. Among these traits, HMCW—marking the transition between the lower and upper crown—is a critical but often overlooked parameter. Its uneven distribution is shaped by directional competition, shading, and branch dieback, making it difficult to measure in dense canopies. While UAV and ground-based LiDAR have improved forest phenotyping, crown overlap still hampers accuracy. Traditional spatial structure analysis methods, such as the nearest four trees (NFT) or Voronoi diagrams, lack the directional precision needed to capture localized competition effects on crown shape. Based on these challenges, the research team sought a more realistic way to map crown interactions and couple them with advanced regression models.

A study (DOI: 10.1016/j.plaphe.2025.100018) published in Plant Phenomics on 28 February 2025 by Huaiqing Zhang’s team, Chinese Academy of Forestry, improves the accuracy of predicting hard-to-measure tree crown traits like HMCW, offering a scalable tool for forest structure analysis and management.

In this study, spatial structure units for 1,943 sample trees were first constructed using the proposed BSETC method, which accounts for crown distribution in four cardinal directions, and compared with the traditional nearest four trees (NFT) and Voronoi methods. The BSETC approach identified 2–8 neighboring trees per unit, versus a fixed four in NFT and 2–10 in Voronoi. Comparative analyses of neighbor selection showed that while all methods rely on inter-tree distances, BSETC achieved higher realism by incorporating crown width, distance, and shading effects, yielding neighbors with genuine spatial interaction. Overlap analysis indicated moderate-to-high similarity between BSETC and NFT (0.4–0.7 range) and lower overlap with Voronoi (0.1–0.4 range), while unique neighbor counts were lowest for BSETC (median=0), moderate for NFT (median=2), and highest for Voronoi (median=5). Similarity and dissimilarity metrics confirmed that BSETC aligns with forestry principles but captures directional competition more precisely. Using these spatial units, 11 machine learning algorithms were trained to couple HMCW with phenotype and competition parameters, with features including tree height, directional crown width, and vertical/horizontal competition indices. Hyperparameters were optimized via GridSearchCV, and evaluation across R², RMSE, MAE, MAPE, EVS, and MedAE identified Random Forest (RF) as the best-performing single model on test data (R² = 0.8186). To further enhance accuracy, five ensemble learning methods (Bagging, Boosting, Voting, Stacking, Blending) generated 10,180 model combinations; 398 exceeded RF’s performance. The top ensemble, a Bagging regressor integrating XGBoost, RF, SVR, GB, and Ridge, achieved R² = 0.8346, RMSE reduced by 6.66%, and EVS improved by 1.63% over RF. This confirmed that ensemble learning, combined with refined spatial structure mapping, provides a more accurate, generalizable solution for predicting HMCW from easily measured parameters.

The approach provides a scalable, non-destructive way to estimate HMCW and other challenging crown traits across species with similar architectures. By enabling more precise canopy morphology simulations, it supports studies on photosynthesis distribution, forest growth modeling, and selective breeding. In practical forestry, it can inform thinning strategies, optimize stand density, and improve timber yield predictions. The methodology also strengthens ecological research by allowing finer-scale coupling between environmental conditions and tree phenotypes, critical for climate change adaptation and biodiversity assessments.

##

References

DOI

10.1016/j.plaphe.2025.100018

Original Source URL

https://doi.org/10.1016/j.plaphe.2025.100018

Funding information

This work was funded by Fundamental Research Funds of CAF (CAFYBB2023PA003), Science and Technology Innovation 2030-Major Projects (2023ZD0406103) and National Natural Science Foundation of China (32271877).

About Plant Phenomics

Science Partner Journal Plant Phenomics is an online-only Open Access journal published in affiliation with the State Key Laboratory of Crop Genetics & Germplasm Enhancement, Nanjing Agricultural University (NAU) and distributed by the American Association for the Advancement of Science (AAAS). Like all partners participating in the Science Partner Journal program, Plant Phenomics is editorially independent from the Science family of journals. Editorial decisions and scientific activities pursued by the journal's Editorial Board are made independently, based on scientific merit and adhering to the highest standards for accurate and ethical promotion of science. These decisions and activities are in no way influenced by the financial support of NAU, NAU administration, or any other institutions and sponsors. The Editorial Board is solely responsible for all content published in the journal. To learn more about the Science Partner Journal program, visit the SPJ program homepage.


 

Texas A&M researchers map America’s power outage hot spots using AI



New nationwide vulnerability index reveals 20% annual increase in outage severity since 2019, with East and West coasts, Great Lakes and Gulf regions facing the highest risk of weather-induced blackouts




Texas A&M University




Hurricane Beryl, Winter Storm Uri and other severe weather events have increased long-term power outages for Texas residents in recent years. But this issue does not just affect Texans. 

Researchers from the Urban Resilience AI Lab at Texas A&M University have used machine learning to create a nationwide Power System Vulnerability Index (PSVI) that identifies areas at increased risk of power outages. 

“Using data from Oak Ridge National Laboratory, we were able to study the effect of weather events on the frequency and duration of nationwide power outages over the past 10 years,” said Dr. Junwei Ma, a postdoctoral researcher in the Zachry Department of Civil and Environmental Engineering. “The dataset included over 179 million data points sorted by time and location, allowing us to create the PSVI.”

The study’s results show an increase in the extent of weather-induced power outages. Trends show an increase in the length and frequency of power outages, with more customers being affected annually.

Authors of this paper — including Ma, his fellow postdoctoral researcher Dr. Bo Li, Dr. Olufemi A. Omitaomu from Oak Ridge National Laboratory, and Dr. Ali Mostafavi, a professor in the Zachry Department of Civil and Environmental Engineering — identified several regions they would consider hot spots, facing the highest levels of power system vulnerability. Hot spots include the East and West Coasts and the Great Lakes and Gulf regions, indicating areas of dense development face higher vulnerability for power outages.

The research team identified the hot spots and annual increase rate trends thanks to their novel and publicly available PSVI map.

“This is an interactive tool that can showcase the overall PSVI ratings and scores of individual U.S. counties over the past decade, and how vulnerability shifts year by year,” said Ma.

Researchers also observed that many AI data centers — like the ones used to store this study’s data — are located in the hot spots, showing the need for increased investments in infrastructure to protect these resources.

By using a type of machine learning called explainable AI, this software goes beyond just sorting data. It can identify trends. This innovation is central to a series of studies on power outage vulnerability from the Urban Resilience AI Lab. Previous studies have revealed growing and disparate vulnerability in the U.S. power system. 

“We knew that the state of power system vulnerability nationwide is exacerbating. But the magnitude of that was shocking, and greater than we hypothesized,” said Mostafavi, who also serves as the director of the Urban Resilience AI Lab. “After 2019, we see a 20% annual increase in outage duration, frequency and magnitude.”

Knowing an area is at-risk allows policymakers to prioritize preparation for long and frequent power outages, reducing associated socioeconomic impacts, such as limited access to food and inability to travel to work. Understanding power system vulnerability is key for stakeholders making decisions that impact community resilience.

By Alyssa Schaechinger, Texas A&M University College of Engineering