Vidyani Suryadevara

All Publications

• Beyond Structure: The Interplay of Bone and Brain During Alzheimer's Disease. Comprehensive Physiology Pinnamaneni, A., Akkiraju, A., Park, H. I., Ch V, R. S., Ayalasomayajula, V., Bandela, M., Kaipa, S., Khosla, S., Zeineh, M., Suryadevara, V. 2025; 15 (6): e70075

  Abstract

  Alzheimer's disease (AD), a leading cause of dementia in the elderly, is traditionally characterized by neurodegeneration driven by amyloid-beta plaques and tau tangles. However, emerging evidence reveals that AD's impact extends beyond the brain, significantly affecting skeletal health. This review integrates clinical and transgenic mouse model data to elucidate the mechanistic interplay between AD pathology and bone metabolism. AD patients exhibit increased risk for hip fractures and low bone mineral density (BMD), independent of cognitive impairment severity. We found altered calcium and alkaline phosphate levels in the blood of patients with mild cognitive impairment and AD, as assessed from the Alzheimer's Disease Neuroimaging Initiative data. Convergent risk factors-age, sex, APOE4 genotype, smoking, and vitamin D deficiency-contribute to both neurodegeneration and bone fragility. Key molecular pathways, such as Wnt/β-catenin signaling and TREM2-mediated osteoclast regulation, underscore shared mechanisms driving disease pathology in both systems. Mouse models of AD consistently demonstrate disrupted bone remodeling, impaired osteoblast function, and heightened osteoclast activity. Therapeutic strategies targeting overlapping pathways, including lithium, anti-FSH antibodies, and NF-κB inhibitors, show promise in mitigating both cognitive decline and bone loss. Collectively, these insights advocate for a more integrated view of AD that includes skeletal comorbidities, potentially guiding the development of dual-purpose interventions.

  View details for DOI 10.1002/cph4.70075

  View details for PubMedID 41310918

• Biomarkers. Alzheimer's & dementia : the journal of the Alzheimer's Association Kaipa, S., Meka, S. R., Nair, R. V., Channappa, D., Oh, H. S., Moran-Losada, P., Rutledge, J. E., Mormino, E., Zeineh, M., Wyss-Coray, T., Henderson, V., Suryadevara, V. 2025; 21 Suppl 2: e104186

  Abstract

  BACKGROUND: Dementia represents a significant health and societal challenge, identified as a primary cause of mortality worldwide and closely associated with the aging population. A 24-year follow up study indicated that socioeconomic status affects the risk of multimorbidity including dementia, frailty, and disability, with multimorbidity showing the strongest association with mortality. There is evidence that fractures pose a risk factor for dementia and individuals with dementia had a higher risk for falls and fractures. The common risk factors for dementia and impaired bone health are aging, ApoE 7, vitamin D and lifestyle choices. To determine if there are global changes in bone health along the progression of AD, we performed a cross-sectional evalution of serum levels of proteins related to bone metabolism.METHODS: Plasma from people wiht Alzheimer's disease (AD, n=95), Mild cognitive impairment (MCI, n=134), and healthy controls (HC, n=394) was used to extract plasma proteins. 2865 proteins were identified after heparin-bound proteins were enriched using heparin affinity chromatography and subsequently subjected to tandem mass spectrometry at Stanford ADRC, followed by filtering for bone markers.RESULTS: In MCI, Collagen A1(VI), WNT16, and OLR1 are upregulated in males whereas IGFBP-1, Ephrin-A2, and IGFBP-1 are downregulated compared to HC. In females, COL is downregulated in MCI compared to HC. On the other hand during AD, bone related proteins Collagen A1(VI) and CHST6 are upregulated in males, whereas FGF-19, IGFBP-1, Chondrocalcin, FGF-19, and IGFBP-1 are downregulated compared to HC. In females, FGF-19 is upregulated and IGFBP-1 and COL are downregulated in AD compared to HC. The senescent markers upregulated in MCI are WNT16 and HGFm whereas IL32 in AD compared to AD patients.CONCLUSIONS: These findings provide evidence of sex-dependent progressive bone tissue alterations, and plasma biomarkers of senescence revealing a potential link between age associated neurodegeneration and bone health.

  View details for DOI 10.1002/alz70856_104186

  View details for PubMedID 41449626

• Public Health. Alzheimer's & dementia : the journal of the Alzheimer's Association Suryadevara, V., Vepakomma, V., Pulivarthi, B., Angadi, K. K., Mangialasche, F., Kivipelto, M., Reddy G, B. 2025; 21 Suppl 6 (Suppl 6): e100057

  Abstract

  Dementia continues to be a growing problem in India, one of the most diverse countries in the world. Dementia is a multi-factorial disorder driven by genetic predisposition and environmental influences, such as nutrition, resulting from lifelong interactions between protective and risk determinants. Modifying or controlling lifestyle-related risk factors through targeted interventions may significantly reduce the risk of developing dementia. In this study, we deployed the most widely used Cardiovascular Risk Factors, Aging, and Incidence of Dementia (CAIDE) risk score for predicting the likelihood of onset of dementia in urban vs rural areas.This study performed at National Institute of Nutrition (NIN), India is community-based cross-sectional study in healthy individuals residing in and around Hyderabad, Telangana, in Southern India. The study included 471 individuals with an equal number of males and females with ages ranging 50-90. This is a collaborative work with investigators form NIN, Worldwide FINGER and Stanford University. Among the various information collected from these individuals, the variables necessary to calculate CAIDE score included age, gender, level of education, BMI, physical activity, systolic blood pressure, and total cholesterol.CAIDE score initially developed by the worldwide FINGER team was optimized to account for parameters specific to Indian population. In this cohort, we considered Individuals with a CAIDE score ≥9.0 to be at risk for onset of dementia. Among the study participants, 40% had a predicted risk of dementia, with a CAIDE score of ≥9.0 (n = 189). The proportion of individuals at risk (CAIDE score ≥9.0) was higher in rural areas (56%) compared to urban areas (28%). One striking difference in the variables between urban and rural cohorts was education levels.The study revealed a higher prevalence of risk for dementia in urban cohorts compared to the rural cohorts. Furthermore, the findings highlight the need for curating region-specific lifestyle interventions to prevent the onset of dementia, given the vast diversity across disciplines.

  View details for DOI 10.1002/alz70860_100057

  View details for PubMedID 41434975

  View details for PubMedCentralID PMC12726281

• Deep learning for accurate tumour volume measurement and prediction of therapy response in paediatric osteosarcoma. European radiology von Krüchten, R., Barrow, M., Adams, L., Singh, S. B., Varniab, Z. S., Suryadevara, V., Ghimire, P., Pribnow, A., Qi, J., Applin, D., Lokesha, Y. U., Nernekli, K., Daldrup-Link, H. E. 2025

  Abstract

  To assess treatment response in osteosarcoma, two automated convolutional neural networks (CNNs) were developed to quantify tumour volumes and predict response to induction chemotherapy using histopathology as the reference standard.This retrospective, multicentre study included magnetic resonance imaging (MRI) scans from osteosarcoma patients acquired between January 2006 and July 2024. A 3D U-Net CNN segmented tumours and calculated volumes at baseline and post-chemotherapy. A second CNN predicted treatment response based on MRI-derived tumour volume changes using histopathologic necrosis (≥ 90%) as the reference standard. Both models were trained on 162 scans from 81 patients (Centre A) and validated on 40 scans from 20 patients (10 per centre) with Centre B as the external test set. Human readers measured 3D tumour diameters and volumes, compared with CNN-derived volumes using Spearman's correlation, Bland-Altman plots, and Dice coefficients. Prediction performance was assessed using accuracy, sensitivity, and specificity, with significance determined by agreement metrics.Patients from Centre A had a mean age of 15 ± 5 years (52 males), and from Centre B a mean age of 13 ± 0 years (8 males). CNN- and human-derived tumour volumes showed strong correlation (Centre A: r = 0.98, Centre B: r = 0.95; p < 0.001). Dice coefficients were 0.86 (Centre A) and 0.81 (Centre B), with median Hausdorff distances of 15.0 mm and 14.2 mm. The response prediction model classified 16/20 cases (80% accuracy) with 90% sensitivity and 70% specificity.CNN-derived tumour volume measurements were comparable to human assessments. CNN-based volume changes predicted histopathologic response to chemotherapy in paediatric osteosarcoma.Question Accurate, noninvasive assessment of treatment response in paediatric osteosarcoma is limited by its reliance on manual tumour measurements and post-surgical histopathology. Findings Automated deep learning accurately measured tumour volumes on MRI and predicted chemotherapy response with 80% accuracy, 90% sensitivity, and 70% specificity. Clinical relevance Automated deep learning enables accurate tumour volume assessment and prediction of chemotherapy response in paediatric osteosarcoma, offering a noninvasive tool to support and refine patient management.

  View details for DOI 10.1007/s00330-025-12115-w

  View details for PubMedID 41176552

  View details for PubMedCentralID 4486345

• Apparent diffusion coefficient can assist in differentiating between benign and malignant primary bone tumors in pediatric patients. Skeletal radiology Lokesha, Y. U., Singh, S. B., von Krüchten, R., Varniab, Z. S., Kumar, M., Suryadevara, V., Sarrami, A. H., Liang, T., Wong, J., Pribnow, A., Daldrup-Link, H. E. 2025

  Abstract

  To evaluate differences in apparent diffusion coefficient (ADC) values between benign and malignant primary pediatric bone tumors and to assess their diagnostic accuracy in differentiating these tumors.We retrospectively analyzed MRI scans of 96 pediatric patients (54 males, 42 females; mean age 12.97 ± 3.9 years) with primary bone tumors who underwent diffusion-weighted imaging, including 48 benign and 48 malignant tumors. We measured ADCmean, ADCmin, and ADCmax of the solid tumor part, carefully avoiding cystic, necrotic, or sclerosed tumor areas. The Wilcoxon rank-sum test was used to test the distributional difference of benign vs malignant tumors. ROC curve analysis was performed to assess the diagnostic accuracy. The optimal cutoff of ADC values to differentiate benign and malignant bone tumors was defined as the point at which the Youden index, the sum of sensitivity and specificity, was maximized.The median values of the ADCmean, ADCmin, and ADCmax for benign bone tumors [1.34 (1.13-1.83), 0.98 (0.73-1.34), and 1.80 (1.57-2.46) × 10-3mm2/s, respectively] were significantly higher compared to malignant bone tumors [0.93 (0.78-1.03), 0.59 (0.43-0.72), and 1.35 (1.22-1.66) × 10-3mm2/s, respectively; all p < 0.05]. ADCmean yielded the highest diagnostic accuracy, with an optimal cutoff of 1.04 (0.94-1.15) × 10-3mm2/s (sensitivity 77%, specificity 93%, AUC = 0.91). An ADCmin cutoff of 0.82 (0.65-0.98) × 10-3mm2/s resulted in a sensitivity of 87.5%, specificity of 70.0%, and AUC of 0.85. An ADCmax cutoff of 1.48 (1.18-1.78) × 10-3mm2/s achieved a sensitivity of 68%, specificity of 81%, and AUC of 0.80.ADCmean, ADCmin, and ADCmax differ significantly between benign and malignant pediatric bone tumors, and the ADCmean provides the highest diagnostic accuracy.

  View details for DOI 10.1007/s00256-025-05060-8

  View details for PubMedID 41160129

  View details for PubMedCentralID 11099578

• Sex differences and the role of estrogens in the immunological underpinnings of Alzheimer's disease. Alzheimer's & dementia (New York, N. Y.) Price, B. R., Walker, K. A., Eissman, J. M., Suryadevara, V., Sime, L. N., Hohman, T. J., Gordon, M. N. 2025; 11 (3): e70139

  Abstract

  Alzheimer's disease (AD) affects women more frequently and more severely than men, but the biological mechanisms underlying these sex differences remain poorly understood. This review integrates recent findings from neuroscience, immunology, endocrinology, and genetics to explore how sex steroid hormones, particularly estrogen, shape neuroimmune responses and influence AD risk. We highlight the pivotal roles of microglia and astrocytes, whose inflammatory and neuroprotective actions are modulated by hormonal fluctuations across the female lifespan, including pregnancy, menopause, and menopausal hormone replacement therapy. Key genetic risk factors, such as apolipoprotein E ε4, show sex-specific effects on glial activation, tau pathology, and cognitive decline. Furthermore, life-stage transitions, especially menopause, intersect with changes in brain metabolism, immune signaling, and epigenetic regulation, increasing susceptibility to neurodegeneration in women. We propose a framework for sex-aware, personalized approaches to AD prevention and treatment. By integrating hormone-immune interactions with genetic and glial biology, this review emphasizes the critical need for sex-specific models in AD research.Women develop greater tauopathy, with more cognitive and clinical consequences in Alzheimer's disease (AD).Glial activation is adapted by estrogens to shape vulnerability or resilience to AD.Sex differences in innate and adaptive immunity could contribute to AD progression.Effects of menopausal hormone therapy on immunity in AD remain understudied.Future studies to explore sex differences in immune function during AD are needed.

  View details for DOI 10.1002/trc2.70139

  View details for PubMedID 40827126

  View details for PubMedCentralID PMC12358009

• Multimorbidity in dementia: Current perspectives and future challenges. Alzheimer's & dementia : the journal of the Alzheimer's Association Stirland, L. E., Choate, R., Zanwar, P. P., Zhang, P., Watermeyer, T. J., Valletta, M., Torso, M., Tamburin, S., Saeed, U., Ridgway, G. R., Moukaled, S., Lusk, J. B., Loi, S. M., Littlejohns, T. J., Kuźma, E., James, S. N., Grande, G., Foote, I. F., Cousins, K. A., Butler, J., AbuHamdia, A., Avelino-Silva, T. J., Suryadevara, V. 2025; 21 (8): e70546

  Abstract

  Multimorbidity-the co-occurrence of two or more chronic health conditions-affects > 86% of people with dementia. It is associated with cognitive and functional decline, reduced health-related quality of life, increased health-care use, and higher mortality. The relationship between multimorbidity and dementia is potentially bidirectional; conditions such as hypertension and diabetes increase the risk of developing dementia, and cognitive impairment can complicate their management. This complexity presents challenges in health care and research, affecting treatment decisions and often leading to the exclusion of these individuals from clinical trials. Understanding multimorbidity through long-term prospective studies is crucial to clarify its relationship with dementia. Investigating specific disease combinations, environmental and genetic factors, and their impacts on cognitive health will guide the development of effective prediction models and inclusive intervention strategies for diverse global populations across the life course. HIGHLIGHTS: Multimorbidity affects > 86% of individuals with dementia, worsening outcomes. The relationship between multimorbidity and dementia is potentially bidirectional. Chronic conditions hinder dementia management and clinical trial inclusion. Life-course multimorbidity research is key to dementia risk reduction strategies. Prospective studies are needed to improve prediction models and interventions.

  View details for DOI 10.1002/alz.70546

  View details for PubMedID 40755143

• What would it take to prove that a chronic infection is a causal agent in Alzheimer's disease? Trends in neurosciences Brutkiewicz, R. R., Cao, W., Morgan, D., Reis, R. S., Suryadevara, V., Willette, A. A., Willette, S. A., Wyatt-Johnson, S. K., Duggan, M. R. 2025

  Abstract

  Accumulating evidence over several years suggests that microbial infections (e.g., bacteria, viruses, fungi) may play a role in the etiology of Alzheimer's disease (AD). In this review, we discuss the reported associations between a variety of microbes and the development of AD, as well as potential causal relationships between infections and AD risk. Having evaluated the current state of knowledge, we make specific recommendations for what it would take to present definitive evidence that chronic infections play a causal role in AD pathogenesis.

  View details for DOI 10.1016/j.tins.2025.05.009

  View details for PubMedID 40527696

• Multinational Attitudes Toward AI in Health Care and Diagnostics Among Hospital Patients. JAMA network open Busch, F., Hoffmann, L., Xu, L., Zhang, L. J., Hu, B., García-Juárez, I., Toapanta-Yanchapaxi, L. N., Gorelik, N., Gorelik, V., Rodriguez-Granillo, G. A., Ferrarotti, C., Cuong, N. N., Thi, C. A., Tuncel, M., Kaya, G., Solis-Barquero, S. M., Mendez Avila, M. C., Ivanova, N. G., Kitamura, F. C., Hayama, K. Y., Puntunet Bates, M. L., Torres, P. I., Ortiz-Prado, E., Izquierdo-Condoy, J. S., Schwarz, G. M., Hofstaetter, J. G., Hide, M., Takeda, K., Peric, B., Pilko, G., Thulesius, H. O., Lindow, T., Kolawole, I. K., Olatoke, S. A., Grzybowski, A., Corlateanu, A., Iaconi, O. S., Li, T., Domitrz, I., Kepczynska, K., Mihalcin, M., Fašaneková, L., Zatonski, T., Fulek, K., Molnár, A., Maihoub, S., da Silva Gama, Z. A., Saba, L., Sountoulides, P., Makowski, M. R., Aerts, H. J., Adams, L. C., Bressem, K. K., Navarro, Á. A., Águas, C., Aineseder, M., Alomar, M., Al Sliman, R., Anand, G., Angkurawaranon, S., Aoki, S., Arkoh, S., Ashraf, G., Astri, Y., Bakhshi, S., Bayramov, N. Y., Billis, A., Bitencourt, A. G., Bolejko, A., Bollas Becerra, A. J., Bwambale, J., Capela, A., Cau, R., Chacon-Acevedo, K. R., Chaunzwa, T. L., Chojniak, R., Clements, W., Cuocolo, R., Dahlblom, V., Sousa, K. d., Villarrubia, J. E., Desai, V. B., Dhakal, A. K., Dignum, V., Andrade, R. G., Ferraioli, G., Ganguly, S., Garg, H., Savevska, C. G., Radovikj, M. G., Gkartzoni, A., Gorospe, L., Griffin, I., Hadamitzky, M., Ndahiro, M. H., Hering, A., Hochhegger, B., Huseynova, M. R., Ishida, F., Jha, N., Jiang, L., Kader, R., Kavnoudias, H., Klein, C., Kolostoumpis, G., Koshy, A., Kruger, N. A., Löser, A., Lucijanic, M., Mantziari, D., Margue, G., McFadden, S., Miyake, M., Morakote, W., Ngabonziza, I., Nguyen, T. T., Niehues, S. M., Nortje, M., Palaian, S., Pentara, N. V., de Almeida, R. P., Poma, G., Purwoko, M., Pyrgidis, N., Rafailidis, V., Rainey, C., Ribeiro, J. C., Agudelo, N. R., Sado, K., Saidman, J. M., Saturno-Hernandez, P. J., Suryadevara, V., Schulz, G. B., Soric, E., Soto-Pérez-Olivares, J., Stanzione, A., Struck, J. P., Takaoka, H., Tanioka, S., Huyen, T. T., Truhn, D., van Dijk, E. H., van Wijngaarden, P., Wang, Y. C., Weidlich, M., Zhang, S. 2025; 8 (6): e2514452

  Abstract

  The successful implementation of artificial intelligence (AI) in health care depends on its acceptance by key stakeholders, particularly patients, who are the primary beneficiaries of AI-driven outcomes.To survey hospital patients to investigate their trust, concerns, and preferences toward the use of AI in health care and diagnostics and to assess the sociodemographic factors associated with patient attitudes.This cross-sectional study developed and implemented an anonymous quantitative survey between February 1 and November 1, 2023, using a nonprobability sample at 74 hospitals in 43 countries. Participants included hospital patients 18 years of age or older who agreed with voluntary participation in the survey presented in 1 of 26 languages.Information sheets and paper surveys handed out by hospital staff and posted in conspicuous hospital locations.The primary outcome was participant responses to a 26-item instrument containing a general data section (8 items) and 3 dimensions (trust in AI, AI and diagnosis, preferences and concerns toward AI) with 6 items each. Subgroup analyses used cumulative link mixed and binary mixed-effects models.In total, 13 806 patients participated, including 8951 (64.8%) in the Global North and 4855 (35.2%) in the Global South. Their median (IQR) age was 48 (34-62) years, and 6973 (50.5%) were male. The survey results indicated a predominantly favorable general view of AI in health care, with 57.6% of respondents (7775 of 13 502) expressing a positive attitude. However, attitudes exhibited notable variation based on demographic characteristics, health status, and technological literacy. Female respondents (3511 of 6318 [55.6%]) exhibited fewer positive attitudes toward AI use in medicine than male respondents (4057 of 6864 [59.1%]), and participants with poorer health status exhibited fewer positive attitudes toward AI use in medicine (eg, 58 of 199 [29.2%] with rather negative views) than patients with very good health (eg, 134 of 2538 [5.3%] with rather negative views). Conversely, higher levels of AI knowledge and frequent use of technology devices were associated with more positive attitudes. Notably, fewer than half of the participants expressed positive attitudes regarding all items pertaining to trust in AI. The lowest level of trust was observed for the accuracy of AI in providing information regarding treatment responses (5637 of 13 480 respondents [41.8%] trusted AI). Patients preferred explainable AI (8816 of 12 563 [70.2%]) and physician-led decision-making (9222 of 12 652 [72.9%]), even if it meant slightly compromised accuracy.In this cross-sectional study of patient attitudes toward AI use in health care across 6 continents, findings indicated that tailored AI implementation strategies should take patient demographics, health status, and preferences for explainable AI and physician oversight into account.

  View details for DOI 10.1001/jamanetworkopen.2025.14452

  View details for PubMedID 40493367

  View details for PubMedCentralID PMC12152705

• MRI detection of senescent cells in porcine knee joints with a β-galactosidase responsive Gd-chelate. Npj imaging Nernekli, K., Mangarova, D. B., Suryadevara, V., Hajipour, M., Tang, J. H., Wang, J., Liang, T., Harris, M., Ueyama, T., Lyons, J. K., Moseley, M. E., Roudi, R., Pisani, L., von Krüchten, R., Duwa, R., Lu-Liang, S. Y., Shokri Varniab, Z., Vasyliv, I., Das, N., Murayama, M., Shinohara, I., Pratx, G., Goodman, S. B., Meade, T. J., Daldrup-Link, H. E. 2025; 3 (1): 18

  Abstract

  Senescent cells promote osteoarthritis progression through the secretion of inflammatory mediators. Preclinical studies have identified senescence-associated beta-galactosidase (β-gal) as a biomarker of senescence, but in vivo detection remains challenging. Here, we evaluated whether a β-gal responsive gadolinium (Gd) chelate can non-invasively detect β-gal expressing senescent cells with standard clinical magnetic resonance imaging (MRI) technology in vitro, ex vivo, and in vivo in porcine joints. In vitro studies showed that senescent mesenchymal stromal cells (MSCs) exhibited significant MRI signal enhancement upon incubation with the β-gal responsive Gd-chelate compared to viable control cells. In vivo, intraarticular injection of the probe into pig knee joints revealed its retention and activation by senescent cells in cartilage defects, evidenced by a significant increase in R 1 relaxation rate. MRI-based senescent cell detection holds promise for identifying patients amenable to senolytic therapies, tailoring treatment plans, and monitoring therapy response in real-time.

  View details for DOI 10.1038/s44303-025-00078-y

  View details for PubMedID 40330124

  View details for PubMedCentralID PMC12049270

• Dual-enzyme activated theranostic nanoparticles for image-guided glioblastoma therapy. Scientific reports Shokri Varniab, Z., Chang, E., Wang, J., Duwa, R., Suryadevara, V., Wu, W., Kumar, M., Liang, T., Khatoon, Z., Morais, G. R., Falconer, R., Shi, Y., Tikhomirov, G., Nernekli, K., Pisani, L. J., Daldrup-Link, H. E. 2025; 15 (1): 13540

  Abstract

  Matrix metalloproteinase-14 (MMP-14) and Cathepsin-B (Cat-B) are overexpressed in glioblastoma (GBM) and not normal brain, making them promising targets for prodrug activation. We investigated a novel combination therapy using two tumor-enzyme activatable theranostic nanoprobes (TNP): TNP-MMP-14, which disrupts the blood tumor barrier via MMP-14 activation, and TNP-Cat-B, which selectively targets GBM cells through Cat-B activation. We hypothesized that combining TNP-MMP-14 and TNP-Cat-B would enhance TNP tumor accumulation and therapeutic efficacy compared to TNP-Cat-B monotherapy. Thirty NSG mice with luciferase-expressing GBM39 tumors received either TNP-MMP-14 plus TNP-Cat-B, TNP-Cat-B only, or saline. Magnetic resonance imaging (MRI) was conducted pre- and post-treatment, with T2* relaxation times analyzed using a generalized linear model. Histopathological differences were assessed using Kruskal-Wallis and Mann-Whitney tests. A Bonferroni correction was applied to account for multiple comparisons. Combination therapy significantly reduced tumor T2* relaxation times (12.98 ± 4.20 ms) compared to TNP-Cat-B monotherapy (22.49 ± 3.95 ms, p < 0.001). The apoptotic marker caspase-3 was also significantly higher in the combination group (64.46 ± 23.43 vs. 15.93 ± 5.81, p < 0.001). These findings demonstrate the potential of dual-enzyme activatable nanoparticles to enhance GBM treatment by overcoming drug delivery barriers and improving therapeutic efficacy over monotherapy.

  View details for DOI 10.1038/s41598-025-97775-w

  View details for PubMedID 40253484

  View details for PubMedCentralID 4490873

• Analysis and interpretation of inflammatory fluid markers in Alzheimer's disease: a roadmap for standardization. Journal of neuroinflammation Bettcher, B. M., de Oliveira, F. F., Willette, A. A., Michalowska, M. M., Machado, L. S., Rajbanshi, B., Borelli, W. V., Tansey, M. G., Rocha, A., Suryadevara, V., Hu, W. T. 2025; 22 (1): 105

  Abstract

  Growing interest in the role of the immune response in Alzheimer's Disease and related dementias (ADRD) has led to widespread use of fluid inflammatory markers in research studies. To standardize the use and interpretation of inflammatory markers in AD research, we build upon prior guidelines to develop consensus statements and recommendations to advance application and interpretation of these markers. In this roadmap paper, we propose a glossary of terms related to the immune response in the context of biomarker discovery/validation, discuss current conceptualizations of inflammatory markers in research, and recommend best practices to address key knowledge gaps. We also provide consensus principles to summarize primary conceptual, methodological, and interpretative issues facing the field: (1) a single inflammatory marker is likely insufficient to describe an entire biological cascade, and multiple markers with similar or distinct functions should be simultaneously measured in a panel; (2) association studies in humans are insufficient to infer causal relationships or mechanisms; (3) neuroinflammation displays time-dependent and disease context-dependent patterns; (4) neuroinflammatory mechanisms should not be inferred based solely on blood inflammatory marker changes; and (5) standardized reporting of CSF inflammatory marker assay validation and performance will improve incorporation of inflammatory markers into the biological AD criteria.

  View details for DOI 10.1186/s12974-025-03432-4

  View details for PubMedID 40234920

  View details for PubMedCentralID 8007081

• IDENTIFICATION OF SENESCENCE IN HUMAN OSTEOARTHRITIS TALUS JOINTS USING NOVEL IMAGING APPROACHES von Kruechten, R., Wrobel, S., Derycz, V., Lerner, C., Dreisbach, A. M., Meade, T., Oji, D., Singh, S., Varniab, Z., Tang, J., Gerencser, A., Suryadevara, V. ELSEVIER SCI LTD. 2025

  View details for Web of Science ID 001481830500054

• PLASMA PROTEOMICS REVEALS CHANGES IN OSTEOARTHRITIS-RELATED PROTEINS DURING ALZHEIMER'S DISEASE. Kaipa, S., Meka, S., Suryadevara, V. ELSEVIER SCI LTD. 2025

  View details for Web of Science ID 001529022600028

• Biomarkers. Alzheimer's & dementia : the journal of the Alzheimer's Association Chintamanibatla, R. R., Mehta, P., Kamarthi, S., Suryadevara, V. 2024; 20 Suppl 2: e093518

  Abstract

  Alzheimer's disease (AD) is a neurodegenerative disorder characterised by cognitive decline and progressive deterioration of brain function. Recent research has suggested a complex interplay between AD and bone health, with individuals affected by AD exhibiting an increased propensity for fractures and falls. Our preclinical studies in PSEN, MAPT P301 S and FDD mice have shown sex-dependent changes in the bone in AD mice, compared to their age-matched wild type mice. To delve deeper into the molecular underpinnings of this relationship, our study leverages data from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database to investigate alterations in bone-specific markers during AD pathology; to unravel potential links between bone metabolism and AD progression.Data from ADNI-1(n=800), ADNI-GO (n=700), ADNI-2 (n=1300) and ADNI-3 (n=2000) was considered for analysis. Spearman correlation analysis was performed between bone markers i.e. calcium and alkaline phosphatase with AD pathology- imaging and cognitive assessment.Calcium levels and alkaline phosphate levels which are critical for bone metabolism were found to be significantly lower in patients with EMCI, LMCI and AD compared to control patients. A negative correlation was found between Calcium levels and Left Hippocampal Volume (Corr Coeff = -0.025, p = 1.38e-19), Right Hippocampal Volume (Corr Coeff = -0.030, p = 1.95e-26), and Montreal Cognitive Assessment (MOCA) scores (Corr Coeff = -0.015, p = 4.34e-08). Alkaline Phosphatase levels show a strong negative correlation with Left Hippocampal Volume (Corr Coeff = -0.075, p = 8.45e-154) and Right Hippocampal Volume (Corr Coeff = -0.078, p = 5.74e-168) and a negative correlation with MOCA scores (Corr Coeff = -0.065, p = 9.02e-118). The negative correlations between Calcium and Alkaline Phosphatase levels with left and right hippocampal volume suggest that lower bone-specific markers are associated with reduced hippocampal volume, elucidating brain-bone crosstalk during AD CONCLUSION: The study reveals correlation between serum bone markers (calcium, alkaline phosphatase) and declining hippocampal volume and cognitive function in Alzheimer's, suggesting a potential link between bone health and AD pathology. This discovery paves the way for deeper understanding and new avenues for diagnosis and treatment.

  View details for DOI 10.1002/alz.093518

  View details for PubMedID 39783911

• Developing Topics. Alzheimer's & dementia : the journal of the Alzheimer's Association Suryadevara, V., Valiya, A. K., Krehbiel, C. J., Karra, S., Kluppel, M., Miller, L., Monte, W. S. 2024; 20 Suppl 8: e095656

  Abstract

  Comorbidities are becoming increasingly evident during various Alzheimer's disease related pathologies. It was found that patients with AD have a higher risk for fractures and falls. Further people who have an incident of falls/fractures have a higher risk for cognitive decline. This study is focused on investigating the alterations in the bone at the structural and functional level in MAPT P301S Tg+ mouse, a preclinical model for frontotemporal dementia.The MAPT P301S Tg+ mouse expresses a human 4-repeat mutant MAPT P301S and was developed to model NFTs secondary to tau aggregations. The femur from N = 20 (equal number of male and female) MAPT P301S Tg+ and C57BL/6J mice at 12-months age were scanned with µCT to characterize the bone microarchitecture. Further three-point bending test was performed to assess the biomechanical properties and FTIR was used to determine the material properties of the bone. The expression of genes regulating the bone matrix composition was determined by using RTPCR.The male MAPT P301S Tg+ mice have a significant decrease in bone geometrical parameters (both cortical and trabecular properties) than the females, as compared to their respective wild type. Interestingly the biomechanical properties were altered in both the males and females, wherein there was an increase in the pre-yield properties, but decrease in the post-yield properties. This correlated with the alterations in the material properties of the male bone determined by FTIR and the changes in the genes regulating the extracellular matrix of the bone. Tauopathies lead to loss of bone structure and functionality by altering it's material composition. Further, we found protein expression CONCLUSION: This is a first study indicating the presence of Tau in the bone, which impacts the function and this opens up the prospective of Tau impacting other organs, in addition or concurrently with neurodegenerative diseases.

  View details for DOI 10.1002/alz.095656

  View details for PubMedID 39783343

• Gender-related alterations in bone observed in PSEN11 L166P knock-in mice, which are linked to a decrease in osteoclast activity and number Suryadevara, V., Krehbial, C., Hong, J., Chester, K. P., Kambrath, A., Kluppel, M., Karra, S., Willis, M. S., Bruzzaniti, A. OXFORD UNIV PRESS. 2024: 96

  View details for Web of Science ID 001361790800277

• SenNet recommendations for detecting senescent cells in different tissues. Nature reviews. Molecular cell biology Suryadevara, V., Hudgins, A. D., Rajesh, A., Pappalardo, A., Karpova, A., Dey, A. K., Hertzel, A., Agudelo, A., Rocha, A., Soygur, B., Schilling, B., Carver, C. M., Aguayo-Mazzucato, C., Baker, D. J., Bernlohr, D. A., Jurk, D., Mangarova, D. B., Quardokus, E. M., Enninga, E. A., Schmidt, E. L., Chen, F., Duncan, F. E., Cambuli, F., Kaur, G., Kuchel, G. A., Lee, G., Daldrup-Link, H. E., Martini, H., Phatnani, H., Al-Naggar, I. M., Rahman, I., Nie, J., Passos, J. F., Silverstein, J. C., Campisi, J., Wang, J., Iwasaki, K., Barbosa, K., Metis, K., Nernekli, K., Niedernhofer, L. J., Ding, L., Wang, L., Adams, L. C., Ruiyang, L., Doolittle, M. L., Teneche, M. G., Schafer, M. J., Xu, M., Hajipour, M., Boroumand, M., Basisty, N., Sloan, N., Slavov, N., Kuksenko, O., Robson, P., Gomez, P. T., Vasilikos, P., Adams, P. D., Carapeto, P., Zhu, Q., Ramasamy, R., Perez-Lorenzo, R., Fan, R., Dong, R., Montgomery, R. R., Shaikh, S., Vickovic, S., Yin, S., Kang, S., Suvakov, S., Khosla, S., Garovic, V. D., Menon, V., Xu, Y., Song, Y., Suh, Y., Dou, Z., Neretti, N. 2024

  Abstract

  Once considered a tissue culture-specific phenomenon, cellular senescence has now been linked to various biological processes with both beneficial and detrimental roles in humans, rodents and other species. Much of our understanding of senescent cell biology still originates from tissue culture studies, where each cell in the culture is driven to an irreversible cell cycle arrest. By contrast, in tissues, these cells are relatively rare and difficult to characterize, and it is now established that fully differentiated, postmitotic cells can also acquire a senescence phenotype. The SenNet Biomarkers Working Group was formed to provide recommendations for the use of cellular senescence markers to identify and characterize senescent cells in tissues. Here, we provide recommendations for detecting senescent cells in different tissues based on a comprehensive analysis of existing literature reporting senescence markers in 14 tissues in mice and humans. We discuss some of the recent advances in detecting and characterizing cellular senescence, including molecular senescence signatures and morphological features, and the use of circulating markers. We aim for this work to be a valuable resource for both seasoned investigators in senescence-related studies and newcomers to the field.

  View details for DOI 10.1038/s41580-024-00738-8

  View details for PubMedID 38831121

  View details for PubMedCentralID 5643029

• Detecting High-Dose Methotrexate-Induced Brain Changes in Pediatric and Young Adult Cancer Survivors Using [18F]FDG PET/MRI: A Pilot Study. Journal of nuclear medicine : official publication, Society of Nuclear Medicine Baratto, L., Singh, S. B., Williams, S. E., Spunt, S. L., Rosenberg, J., Adams, L., Suryadevara, V., Iv, M., Daldrup-Link, H. 2024

  Abstract

  Significant improvements in treatments for children with cancer have resulted in a growing population of childhood cancer survivors who may face long-term adverse outcomes. Here, we aimed to diagnose high-dose methotrexate-induced brain injury on [18F]FDG PET/MRI and correlate the results with cognitive impairment identified by neurocognitive testing in pediatric cancer survivors. Methods: In this prospective, single-center pilot study, 10 children and young adults with sarcoma (n = 5), lymphoma (n = 4), or leukemia (n = 1) underwent dedicated brain [18F]FDG PET/MRI and a 2-h expert neuropsychologic evaluation on the same day, including the Wechsler Abbreviated Scale of Intelligence, second edition, for intellectual functioning; Delis-Kaplan Executive Function System (DKEFS) for executive functioning; and Wide Range Assessment of Memory and Learning, second edition (WRAML), for verbal and visual memory. Using PMOD software, we measured the SUVmean, cortical thickness, mean cerebral blood flow (CBFmean), and mean apparent diffusion coefficient of 3 different cortical regions (prefrontal cortex, cingulate gyrus, and hippocampus) that are routinely involved during the above-specified neurocognitive testing. Standardized scores of different measures were converted to z scores. Pairs of multivariable regression models (one for z scores < 0 and one for z scores > 0) were fitted for each brain region, imaging measure, and test score. Heteroscedasticity regression models were used to account for heterogeneity in variances between brain regions and to adjust for clustering within patients. Results: The regression analysis showed a significant correlation between the SUVmean of the prefrontal cortex and cingulum and DKEFS-sequential tracking (DKEFS-TM4) z scores (P = 0.003 and P = 0.012, respectively). The SUVmean of the hippocampus did not correlate with DKEFS-TM4 z scores (P = 0.111). The SUVmean for any evaluated brain regions did not correlate significantly with WRAML-visual memory (WRAML-VIS) z scores. CBFmean showed a positive correlation with SUVmean (r = 0.56, P = 0.01). The CBFmean of the cingulum, hippocampus, and prefrontal cortex correlated significantly with DKEFS-TM4 (all P < 0.001). In addition, the hippocampal CBFmean correlated significantly with negative WRAML-VIS z scores (P = 0.003). Conclusion: High-dose methotrexate-induced brain injury can manifest as a reduction in glucose metabolism and blood flow in specific brain areas, which can be detected with [18F]FDG PET/MRI. The SUVmean and CBFmean of the prefrontal cortex and cingulum can serve as quantitative measures for detecting executive functioning problems. Hippocampal CBFmean could also be useful for monitoring memory problems.

  View details for DOI 10.2967/jnumed.123.266760

  View details for PubMedID 38575193

• Musculoskeletal imaging of senescence. Skeletal radiology Daldrup-Link, H. E., Suryadevara, V., Tanyildizi, Y., Nernekli, K., Tang, J. H., Meade, T. J. 2024

  Abstract

  Senescent cells play a vital role in the pathogenesis of musculoskeletal (MSK) diseases, such as chronic inflammatory joint disorders, rheumatoid arthritis (RA), and osteoarthritis (OA). Cellular senescence in articular joints represents a response of local cells to persistent stress that leads to cell-cycle arrest and enhanced production of inflammatory cytokines, which in turn perpetuates joint damage and leads to significant morbidities in afflicted patients. It has been recently discovered that clearance of senescent cells by novel "senolytic" therapies can attenuate the chronic inflammatory microenvironment of RA and OA, preventing further disease progression and supporting healing processes. To identify patients who might benefit from these new senolytic therapies and monitor therapy response, there is an unmet need to identify and map senescent cells in articular joints and related musculoskeletal tissues. To fill this gap, new imaging biomarkers are being developed to detect and characterize senescent cells in human joints and musculoskeletal tissues. This review article will provide an overview of these efforts. New imaging biomarkers for senescence cells are expected to significantly improve the specificity of state-of-the-art imaging technologies for diagnosing musculoskeletal disorders.

  View details for DOI 10.1007/s00256-024-04585-8

  View details for PubMedID 38329533

  View details for PubMedCentralID 5785239

• Doxorubicin induced senescence in the knee, a new mouse model to study degenerative arthritis Suryadevara, V., Hajipour, M., Martin, A., Habte, F., Malik, N., Chang, E., Mangarova, D., Nernekli, K., Baratto, L., Adams, L. C., Cotton, J., Pichler, B., Beziere, N., Daldrup-Link, H. OXFORD UNIV PRESS. 2023: 409

  View details for Web of Science ID 001266167002095

• Spatial mapping of cellular senescence: emerging challenges and opportunities. Nature aging Gurkar, A. U., Gerencser, A. A., Mora, A. L., Nelson, A. C., Zhang, A. R., Lagnado, A. B., Enninful, A., Benz, C., Furman, D., Beaulieu, D., Jurk, D., Thompson, E. L., Wu, F., Rodriguez, F., Barthel, G., Chen, H., Phatnani, H., Heckenbach, I., Chuang, J. H., Horrell, J., Petrescu, J., Alder, J. K., Lee, J. H., Niedernhofer, L. J., Kumar, M., Konigshoff, M., Bueno, M., Sokka, M., Scheibye-Knudsen, M., Neretti, N., Eickelberg, O., Adams, P. D., Hu, Q., Zhu, Q., Porritt, R. A., Dong, R., Peters, S., Victorelli, S., Pengo, T., Khaliullin, T., Suryadevara, V., Fu, X., Bar-Joseph, Z., Ji, Z., Passos, J. F. 2023

  Abstract

  Cellular senescence is a well-established driver of aging and age-related diseases. There are many challenges to mapping senescent cells in tissues such as the absence of specific markers and their relatively low abundance and vast heterogeneity. Single-cell technologies have allowed unprecedented characterization of senescence; however, many methodologies fail to provide spatial insights. The spatial component is essential, as senescent cells communicate with neighboring cells, impacting their function and the composition of extracellular space. The Cellular Senescence Network (SenNet), a National Institutes of Health (NIH) Common Fund initiative, aims to map senescent cells across the lifespan of humans and mice. Here, we provide a comprehensive review of the existing and emerging methodologies for spatial imaging and their application toward mapping senescent cells. Moreover, we discuss the limitations and challenges inherent to each technology. We argue that the development of spatially resolved methods is essential toward the goal of attaining an atlas of senescent cells.

  View details for DOI 10.1038/s43587-023-00446-6

  View details for PubMedID 37400722

• Thwarting Alzheimer's Disease through Healthy Lifestyle Habits: Hope for the Future. Neurology international Govindugari, V. L., Golla, S., Reddy, S. D., Chunduri, A., Nunna, L. S., Madasu, J., Shamshabad, V., Bandela, M., Suryadevara, V. 2023; 15 (1): 162-187

  Abstract

  Alzheimer's disease (AD) is a neurodegenerative disorder that slowly disintegrates memory and thinking skills. Age is known to be the major risk factor in AD, but there are several nonmodifiable and modifiable causes. The nonmodifiable risk factors such as family history, high cholesterol, head injuries, gender, pollution, and genetic aberrations are reported to expediate disease progression. The modifiable risk factors of AD that may help prevent or delay the onset of AD in liable people, which this review focuses on, includes lifestyle, diet, substance use, lack of physical and mental activity, social life, sleep, among other causes. We also discuss how mitigating underlying conditions such as hearing loss and cardiovascular complications could be beneficial in preventing cognitive decline. As the current medications can only treat the manifestations of AD and not the underlying process, healthy lifestyle choices associated with modifiable factors is the best alternative strategy to combat the disease.

  View details for DOI 10.3390/neurolint15010013

  View details for PubMedID 36810468

• MegaPro, a clinically translatable nanoparticle for in vivo tracking of stem cell implants in pig cartilage defects. Theranostics Suryadevara, V., Hajipour, M. J., Adams, L. C., Aissaoui, N. M., Rashidi, A., Kiru, L., Theruvath, A. J., Huang, C., Maruyama, M., Tsubosaka, M., Lyons, J. K., Wu, W. E., Roudi, R., Goodman, S. B., Daldrup-Link, H. E. 2023; 13 (8): 2710-2720

  Abstract

  Rationale: Efficient labeling methods for mesenchymal stem cells (MSCs) are crucial for tracking and understanding their behavior in regenerative medicine applications, particularly in cartilage defects. MegaPro nanoparticles have emerged as a potential alternative to ferumoxytol nanoparticles for this purpose. Methods: In this study, we employed mechanoporation to develop an efficient labeling method for MSCs using MegaPro nanoparticles and compared their effectiveness with ferumoxytol nanoparticles in tracking MSCs and chondrogenic pellets. Pig MSCs were labeled with both nanoparticles using a custom-made microfluidic device, and their characteristics were analyzed using various imaging and spectroscopy techniques. The viability and differentiation capacity of labeled MSCs were also assessed. Labeled MSCs and chondrogenic pellets were implanted into pig knee joints and monitored using MRI and histological analysis. Results: MegaPro-labeled MSCs demonstrated shorter T2 relaxation times, higher iron content, and greater nanoparticle uptake compared to ferumoxytol-labeled MSCs, without significantly affecting their viability and differentiation capacity. Post-implantation, MegaPro-labeled MSCs and chondrogenic pellets displayed a strong hypointense signal on MRI with considerably shorter T2* relaxation times compared to adjacent cartilage. The hypointense signal of both MegaPro- and ferumoxytol-labeled chondrogenic pellets decreased over time. Histological evaluations showed regenerated defect areas and proteoglycan formation with no significant differences between the labeled groups. Conclusion: Our study demonstrates that mechanoporation with MegaPro nanoparticles enables efficient MSC labeling without affecting viability or differentiation. MegaPro-labeled cells show enhanced MRI tracking compared to ferumoxytol-labeled cells, emphasizing their potential in clinical stem cell therapies for cartilage defects.

  View details for DOI 10.7150/thno.82620

  View details for PubMedID 37215574

• NIH SenNet Consortium to map senescent cells throughout the human lifespan to understand physiological health NATURE AGING Lee, P. J., Benz, C. C., Blood, P., Boerner, K., Campisi, J., Chen, F., Daldrup-Link, H., De Jager, P., Ding, L., Duncan, F. E., Eickelberg, O., Fan, R., Finkel, T., Furman, D., Garovic, V., Gehlenborg, N., Glass, C., Heckenbach, I., Joseph, Z., Katiyar, P., Kim, S., Koenigshoff, M., Kuchel, G. A., Lee, H., Lee, J., Ma, J., Ma, Q., Melov, S., Metis, K., Mora, A. L., Musi, N., Neretti, N., Passos, J. F., Rahman, I., Rivera-Mulia, J., Robson, P., Rojas, M., Roy, A. L., Scheibye-Knudsen, M., Schilling, B., Shi, P., Silverstein, J. C., Suryadevara, V., Xie, J., Wang, J., Wong, A., Niedernhofer, L. J., Wang, S., Anvari, H., Balough, J., Benz, C., Bons, J., Brenerman, B., Evans, W., Gerencser, A., Gregory, H., Hansen, M., Justice, J., Kapahi, P., Murad, N., O'Broin, A., Pavone, M., Powell, M., Scott, G., Shanes, E., Shankaran, M., Verdin, E., Winer, D., Wu, F., Adams, A., Blood, P. D., Bueckle, A., Cao-Berg, I., Chen, H., Davis, M., Filus, S., Hao, Y., Hartman, A., Hasanaj, E., Helfer, J., Herr, B., Bar Joseph, Z., Molla, G., Mou, G., Puerto, J., Quardokus, E. M., Ropelewski, A. J., Ruffalo, M., Satija, R., Schwenk, M., Scibek, R., Shirey, W., Sibilla, M., Welling, J., Yuan, Z., Bonneau, R., Christiano, A., Izar, B., Menon, V., Owens, D. M., Phatnani, H., Smith, C., Suh, Y., Teich, A. F., Bekker, V., Chan, C., Coutavas, E., Hartwig, M. G., Ji, Z., Nixon, A. B., Dou, Z., Rajagopal, J., Slavov, N., Holmes, D., Jurk, D., Kirkland, J. L., Lagnado, A., Tchkonia, T., Abraham, K., Dibattista, A., Fridell, Y., Howcroft, T., Jhappan, C., Montes, V., Prabhudas, M., Resat, H., Taylor, V., Kumar, M., Cigarroa, F., Cohn, R., Cortes, T. M., Courtois, E., Chuang, J., Dave, M., Domanskyi, S., Enninga, E., Eryilmaz, G., Espinoza, S. E., Gelfond, J., Kirkland, J., Kuo, C., Lehman, J. S., Aguayo-Mazzucato, C., Meves, A., Rani, M., Sanders, S., Thibodeau, A., Tullius, S. G., Ucar, D., White, B., Wu, Q., Xu, M., Yamaguchi, S., Assarzadegan, N., Cho, C., Hwang, I., Hwang, Y., Xi, J., Adeyi, O. A., Aliferis, C. F., Bartolomucci, A., Dong, X., DuFresne-To, M. J., Ikramuddin, S., Johnson, S. G., Nelson, A. C., Revelo, X. S., Trevilla-Garcia, C., Sedivy, J. M., Thompson, E. L., Robbins, P. D., Wang, J., Aird, K. M., Alder, J. K., Beaulieu, D., Bueno, M., Calyeca, J., Chamucero-Millaris, J. A., Chan, S. Y., Chung, D., Corbett, A., Gorbunova, V., Gowdy, K. M., Gurkar, A., Horowitz, J. C., Hu, Q., Kaur, G., Khaliullin, T. O., Lafyatis, R., Lanna, S., Li, D., Ma, A., Morris, A., Muthumalage, T. M., Peters, V., Pryhuber, G. S., Reader, B. F., Rosas, L., Sembrat, J. C., Shaikh, S., Shi, H., Stacey, S. D., St Croix, C., Wang, C., Wang, Q., Watts, A., Gu, L., Lin, Y., Rabinovitch, P. S., Sweetwyne, M. T., Artyomov, M. N., Ballentine, S. J., Chheda, M. G., Davies, S. R., DiPersio, J. F., Fields, R. C., Fitzpatrick, J. A. J., Fulton, R. S., Imai, S., Jain, S., Ju, T., Kushnir, V. M., Link, D. C., Ben Major, M., Oh, S. T., Rapp, D., Rettig, M. P., Stewart, S. A., Veis, D. J., Vij, K. R., Wendl, M. C., Wyczalkowski, M. A., Craft, J. E., Enninful, A., Farzad, N., Gershkovich, P., Halene, S., Kluger, Y., VanOudenhove, J., Xu, M., Yang, J., Yang, M., SenNet Consortium 2022; 2 (12): 1090-1100

  View details for DOI 10.1038/s43587-022-00326-5

  View details for Web of Science ID 000916582800010