Shreeram Akilesh
· Associate ProfessorVerifiedUniversity of Washington · Pathology
Active 1999–2026
About
Shreeram Akilesh, MD, PhD, is an Associate Professor in the Department of Laboratory Medicine and Pathology at the University of Washington and serves as the Medical Director of the Immunofluorescence Laboratory and Director of the Digital Spatial Profiling Core Facility. His research focuses on applying next-generation genomic tools and analyses to understand the development, structure, and function of the kidney and its component cells in health and disease. He has received the Damon Runyon Cancer Research Fellowship to support these studies. Dr. Akilesh's clinical and research background includes a fellowship in Renal Pathology, and his academic appointments include roles as Assistant Professor and now Associate Professor at the University of Washington. His educational background includes an MD and PhD in Immunology from Washington University in St. Louis, along with extensive training in pathology, including residency at Barnes-Jewish Hospital. His work emphasizes advancing knowledge in renal pathology through innovative genomic research and clinical expertise.
Research topics
- Medicine
- Biology
- Genetics
- Internal medicine
- Pathology
- Cell biology
- Evolutionary biology
- Cancer research
- Endocrinology
- Immunology
- Computational biology
- Gastroenterology
Selected publications
2026-02-03
articleOpen access<p>Supplemental Figure S9. Role of macrophage:Th:CTL three-cell-type clusters.</p>
2026-02-03
articleOpen access<p>Supplemental Figure S7. Triads are enriched for functional cell types in other spatial transcriptomics datasets.</p>
2026-02-03
articleOpen access<p>Supplemental Figure S3. Cell type annotation for PDAC scRNAseq data.</p>
Gastroenterology · 2026-02-17 · 2 citations
article2026-02-03
articleOpen access<p>Supplemental Figure S5. Spatial transcriptomics of CRC and NSCLC using Xenium immuno-oncology panel.</p>
2026-02-03
articleOpen access<p>Supplemental Figure S13. Comparison of overall survival between tissue microarray and The Cancer Genome Atlas PDAC datasets.</p>
Zero-Shot Chain-of-Thought Reasoning for Cryptanalysis of Popular Ciphers
2026-01-31
article1st authorCorrespondingTechniques of breaking encryptions are becoming increasingly advanced as encryption methods also change. Cryptanalysis normally depends on algorithmic, statistical or brute force attacks targeting ciphers. But now Large Language Models (LLMs) can be used to provide a new method of chain-of-thought (CoT) reasoning. They can make any effort to find solutions to cryptographic problems by logical deduction rather than brute-force search. This study is a test of the effectiveness of zero-shot CoT reasoning in decryption of both classical and modern ciphers. Three best reasoning models were tested: The O1 of OpenAI, the Gemini Thinking of Google, and DeepSeek R1. They had the job of cracking a variety of cryptographic systems, including classical ciphers such as Caesar, Vigenère and Playfair, as well as abstract block ciphers and hash codes. We noted that these LLMs are extremely effective in cracking less complicated ciphers wherein they can locate designs and leverage linguistic hints. Nevertheless, they do not perform well in comparison with modern cryptographic systems that rely on mathematical hardness.
Clinical Kidney Journal · 2026-02-04
articleOpen accessBackground: Kidney biopsy is the gold standard for lupus nephritis (LN) diagnosis, with the 2018 International Society of Nephrology (ISN)/Renal Pathology Society (RPS) histopathological classification widely used for prognosis and treatment decisions. A survey assessing the use of the 2018 ISN/RPS classification in daily practice was recently conducted on behalf of the RPS. Methods: An online survey was sent to active RPS members after a webinar that introduced RPS members to the topic. The survey contained multiple choice and open-ended questions and remained open 30 days for completion. Results were analysed anonymously. Results: Of 562 RPS members, 185 (32.9%) replied to the questionnaire; 180 (97.8%) were pathologists and 120 of these (64.8%) indicated they encounter >20 biopsies with LN per year. The 2018 ISN/RPS classification and the modified National Institutes of Health activity/chronicity indices are used by 92.4% and 88.1% of respondents, respectively. Respondents rated the utility of both systems with a median score of 8 (interquartile range 7-9) on a 1-10 scale. Suggested improvements to the current classification system include greater standardization and simplicity, clearer definitions for grey-zone entities and the introduction of guidelines for new parameters and biomarkers. Conclusions: This study shows that the 2018 ISN/RPS LN classification is widely used in everyday practice by pathologists. Our results highlight the need for ongoing refinement to facilitate targeted treatment decisions, particularly considering evolving phenotypes and therapeutic advancements in LN.
2026-02-03
articleOpen access<p>Supplemental Figure S6. DC:Th:CTL three-cell-clusters are present within and outside of lymphoid aggregates.</p>
2026-02-03
articleOpen access<p>Supplemental Figure S10. Role of APC:Treg:CTL three-cell-type clusters.</p>
Frequent coauthors
- 170 shared
Sanjeev Sethi
- 170 shared
Andréy S. Shaw
- 167 shared
Joseph P. Gaut
Washington University in St. Louis
- 166 shared
Mariam P. Alexander
Mayo Clinic
- 162 shared
Naoki Takahashi
Japanese Foundation For Cancer Research
- 162 shared
Sanjay Jain
University of Oxford
- 162 shared
Marwan Mounayar
Indiana University Health
- 162 shared
Sherif A. Nasr
Education
M.D.
University of Washington
Ph.D.
University of Washington
Awards & honors
- Damon Runyon Cancer Research Fellowship (2013-2016)
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