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Record W6987540149

Successful Outcome of a Patient with Concomitant Pancreatic and Renal Carcinoma Receiving Secoisolariciresinol Diglucoside Therapy Alone: A Case Report

2024· article· en· W6987540149 on OpenAlexaboutno aff

Bibliographic record

VenueDOAJ (DOAJ: Directory of Open Access Journals) · 2024
Typearticle
Languageen
FieldArts and Humanities
TopicRenaissance and Early Modern Studies
Canadian institutionsnot available
Fundersnot available
KeywordsPharmacogenomicsCancerConcomitantNatural medicineTemsirolimusMalignancyAlternative medicine
DOInot available

Abstract

fetched live from OpenAlex

Hao Wu,1– 6 Xing-Hua Zhang,1,3– 6 Li-Ping Wang,7,8 Hong-Da Tian,1,3– 6 Gui-Rong Liu,1,3– 6 Dong-Hui Yang,9 Shu-Lin Liu1,3– 8,10 1Genomics Research Center (State-Province Key Laboratory of Biomedicine-Pharmaceutics of China), College of Pharmacy, Harbin Medical University, Harbin, People’s Republic of China; 2Key Laboratory of Tumor Biotherapy of Heilongjiang Province, Harbin Medical University Cancer Hospital, Harbin, People’s Republic of China; 3Key Laboratory of Gut Microbiota and Pharmacogenomics of Heilongjiang Province, Harbin Medical University, Harbin, People’s Republic of China; 4National Key Laboratory of Frigid Zone Cardiovascular Diseases, Harbin, People’s Republic of China; 5Heilongjiang Academy of Medical Sciences, Harbin Medical University, Harbin, People’s Republic of China; 6Translational Medicine Research and Cooperation Center of Northern China, Harbin Medical University, Harbin, People’s Republic of China; 7KangYuan Hospital, Harbin, People’s Republic of China; 8Xun-Qi Medicine Clinic, Harbin, People’s Republic of China; 9State Key Laboratory of Natural and Biomimetic Drugs, School of Pharmaceutical Sciences, Peking University, Beijing, People’s Republic of China; 10Department of Microbiology, Immunology and Infectious Diseases, University of Calgary, Calgary, CanadaCorrespondence: Shu-Lin Liu, Genomics Research Center, College of Pharmacy, Harbin Medical University, Harbin, 150081, People’s Republic of China, Email slliu@hrbmu.edu.cn Dong-Hui Yang, State Key Laboratory of Natural and Biomimetic Drugs, School of Pharmaceutical Sciences, Peking University, Beijing, 100191, People’s Republic of China, Email ydhui@bjmu.edu.cnIntroduction: Pancreatic cancer (PC) is among the deadliest malignancies. Kidney cancer (KC) is a common malignancy globally. Chemo- or radio-therapies are not very effective to control PC or KC, and overdoses often cause severe site reactions to the patients. As a result, novel treatment strategies with high efficacy but without toxic side effects are urgently desired. Secoisolariciresinol diglucoside (SDG) belongs to plant lignans with potential anticancer activities, but clinical evidence is not available in PC or KC treatment.Patient Concerns: We report a rare case of an 83-year-old female patient with pancreatic and kidney occupying lesions that lacked the conditions to receive surgery or chemo- or radiotherapy.Diagnosis: Pancreatic and kidney cancers.Interventions: We gave dietary SDG to the patient as the only therapeutics.Outcomes: SDG effectively halted progression of both PC and KC. All clinical manifestations, including bad insomnia, loss of appetite, stomach symptoms, and skin itching over the whole body, all disappeared. The initial massive macroscopic hematuria became microscopic and infrequent, and other laboratory results also gradually returned to normal. Most of the cancer biomarkers, initially high such as CEA, CA199, CA724, CA125, came down rapidly, among which CA199 changed most radically. This patient has had progression-free survival of one year so far.Conclusion: These results demonstrate the potent inhibitory effects of SDG on PC and KC of this patient and provide promising novel therapeutics for refractory malignant tumors. Keywords: pancreatic cancer, kidney cancer, lignans, secoisolariciresinol diglucoside, CA199

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Scholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.070
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0020.002
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.203
GPT teacher head0.460
Teacher spread0.257 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2024
Admission routes1
Has abstractyes

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