Schizophrenia and Major Depressive Disorder (MDD) are highly burdensome mental disorders, with significant cost to both individuals and society. Despite these disorders representing distinct clinical ...categories, they are each heterogenous in their symptom profiles, with considerable transdiagnostic features. Although movement and sleep abnormalities exist in both disorders, little is known of the precise nature of these changes longitudinally. Passively-collected longitudinal data from wearable sensors is well suited to characterize naturalistic features which may cross traditional diagnostic categories (e.g., highlighting behavioral markers not captured by self-report information).
The present analyses utilized raw minute-level actigraphy data from three diagnostic groups: individuals with schizophrenia (N = 23), individuals with depression (N = 22), and controls (N = 32), respectively, to interrogate naturalistic behavioral differences between groups. Subjects' week-long actigraphy data was processed without diagnostic labels via unsupervised machine learning clustering methods, in order to investigate the natural bounds of psychopathology. Further, actigraphic data was analyzed across time to determine timepoints influential in model outcomes.
We find distinct actigraphic phenotypes, which differ between diagnostic groups, suggesting that unsupervised clustering of naturalistic data aligns with existing diagnostic constructs. Further, we found statistically significant inter-group differences, with depressed persons showing the highest behavioral variability.
However, diagnostic group differences only consider biobehavioral trends captured by raw actigraphy information.
Passively-collected movement information combined with unsupervised deep learning algorithms shows promise in identifying naturalistic phenotypes in individuals with mental health disorders, specifically in discriminating between MDD and schizophrenia.
•UMAP allows for identification of naturalistic behavioral phenotypes.•Distinct actigraphic phenotypes exist and differ between diagnostic groups.•Depressed persons show highest behavioral variability.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Natural killer cells are a potent effector lymphocyte subset that can induce cytotoxicity without the need for antigen sensitization or presentation. NK cells are a tempting target –for immune ...therapy, monoclonal antibody, or genetic engineering-to enhance immune surveillance mechanisms against myeloma cells.
We hypothesized an association between natural killer cell recovery after autologous stem cell transplantation (ASCT) and disease outcomes in multiple myeloma patients.
We concluded a prospective study that started enrolling patients in January 2020 to identify the association between absolute NK cell count two to three after ASCT and disease outcomes after autologous stem cell transplantation in multiple myeloma using univariate and multivariate analysis.
Natural killer cell recovery was evaluated during the third month after ASCT, day +60 to +90 post-ASCT. Our patients had a mean NK cell count of 90.53, ranging from 14 to 282 Cell/μL (Std Dev 84.64 Cell/μL). The odds of having a minimal residual disease (MRD-positivity) among patients with partial remission before transplantation is four times higher than patients with very good partial response or better (95% confidence interval 0.45–35.79). Our patients were classified into two groups based on MRD status after ASCT, an MRD-negative group of eight participants and an MRD-positive group of seven participants. The mean absolute NK cell count was significantly higher in the MRD-negative cohort, 131.38 Cell/μL, versus 43.86 Cell/μL in the MRD-positive group (p = 0.049).
We conclude that for multiple myeloma patients treated with ASCT, high absolute NK cell counts two to three months after ASCT is an independent predictor for MRD negativity.
•High absolute NK cell counts two to three months after autologous stem cell transplantation is an independent predictor for MRD negativity.•A moderate linear correlation exists between NK cell count and ALC 60–90 days after transplantation.•The odds of MRD negativity were 7.5 higher for patients with normal absolute NK cells than those with low NK cell count (<76 cell/L; 95% confidence interval 5.21–9.79).•The state of MRD negatively affects immune reconstitution after ASCT potentially due to disrupted bone marrow microenvironment that is affecting both proliferation and effector function of T and NK cells.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Introduction
The rhinoplasty butterfly graft is used to improve the internal nasal valve (INV), but post‐operative visibility remains a concern. Intraoperative techniques have developed to thin the ...graft with unknown effect on functionality.
Objectives
Improve understanding of how to modify the aesthetics of the butterfly graft without impacting patient outcomes. Determine how graft contouring affects its biomechanical properties.
Methods
Cadaveric cartilage grafts were used to examine the biomechanics in its native state and with progressive thinning. The force needed to stabilize the INV in an unaltered state and the resistance force provided by native (original), partially thinned, and fully thinned cartilage grafts were recorded.
Results
The mean thickness of grafts in their natural state was 1.64 mm, median 1.50 mm (SD 0.64 mm). The fully‐thinned mean was 0.84 mm, median 0.8 mm (SD 0.18 mm). The mean force (N) of the native graft was 0.74 N and 0.60 N for fully thin (p = 0.016, 95%). The mean force (N) needed to stabilize the INV was 0.15 N (right) and 0.19 N (left).
Conclusion
Butterfly grafts can be thinned by approximately 50% of their original thickness and retain the strength to stabilize the INV.
Level of Evidence
NA Laryngoscope, 134:1638–1641, 2024
The rhinoplasty butterfly graft is used to improve nasal obstruction, but post‐operative visibility remains a concern, and so intraoperative techniques have developed to thin the graft. Our study used cadaveric specimens to test the strength of the thinned grafts, and found that they can be thinned 50% although still stabilizing the internal nasal valve.
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BFBNIB, FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SAZU, SBCE, SBMB, UL, UM, UPUK
Severe acute respiratory distress syndrome coronavirus 2 (SARS-CoV-2) is the cause of the current coronavirus disease of 2019 (COVID-19) pandemic, a tremendous cause of morbidity and mortality ...worldwide. Although there are numerous trials underway, there is currently no medication known to cure the infection. Non-steroidal anti-inflammatory drugs (NSAIDs) are inexpensive, widely available medications with antiviral and anti-inflammatory properties, and may have utility as an adjunct therapy to improve outcomes in patients with severe COVID-19 infection. A thorough PubMed literature review on the therapeutic use of NSAID was conducted to provide a comprehensive perspective of the role of NSAIDs in treating COVID-19. NSAIDs may be a useful adjunct therapy for patients with severe COVID-19 infection, but further investigation and clinical trials are necessary to ensure their safety and efficacy.
•A nested stochastic compound distribution (NSCD) is introduced to analyze the extreme sea states in typhoon-prone areas.•The applicability of the NSCD model in the South China Sea is discussed.•The ...NSCD model is found to be a better model to consider the impact of typhoon in different time periods.•It is shown that the NSCD model has a broader scope of application than existing models.
Extreme sea conditions are often caused by typhoons that occur obviously in season. How to calculate the design values of marine environmental elements based on statistical characteristic of typhoon in different periods is important. A nested stochastic compound distribution (NSCD) model is proposed based on the stochastic process theory. During a typhoon occurrence, the distributions of the marine environmental elements such as wind velocity (WV) and storm surge (SS) at any moment are described in continuous stochastic processes, and the distribution of typhoon occurrence frequency (TOF) during any period is described by a discrete stochastic process. Based on the measured data in the South China Sea (SCS), the applicability of different marginal distribution functions and Copula functions in the SCS are further discussed, and the specific form of the NSCD model suitable for the SCS is obtained. The Design values of WV and SS for different joint return periods and coincidence return periods are calculated according to the NSCD and the compound extreme value distribution (CEVD). The effects of treating TOF as a stochastic process and a random variable on the design values of the two marine environmental elements are discussed. Results show that the NSCD model contains the traditional CEVD model, which is a form of the NSCD model in a specific time situation. The design values of WV and SS obtained by the NSCD model can reflect the impact of TOF on marine environmental elements. Moreover, the probability of simultaneous occurrence of extreme WV and extreme SS is higher over longer return periods under the influence of typhoons. The NSCD model can therefore be used to make joint probability predictions for a wide range of extreme sea conditions in different time periods according to engineering needs.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Preeclampsia poses a cardiovascular disease risk. Abnormal lipid metabolism is important in the pathogenesis of preeclampsia. Dyslipidemia is strongly associated with atherosclerotic cardiovascular ...disease (ASCVD) and has a direct effect on endothelial function. Elevated serum or plasma low density lipoprotein cholesterol (LDL-C), small dense LDL-C (sdLDL-C) and lipoprotein (a) Lp(a) levels are known independent risk factors for ASCVD, however, extensive lipid changes in preeclampsia are incompletely characterized.
This study sought to characterize serum and plasma lipoproteins in preeclampsia and control subjects.
Frozen serum and plasma from pregnant patients enrolled in the Child Health Advances from Research with Mothers (CHARM) study. Visit 1, 30 cases, 89 controls, gestational age 89 days (36d-247d) and Visit 2, 22 cases, 64 controls, gestational age 189 days (136d-256d), were shipped to Boston Heart Diagnostics for blinded analysis. Patients with gestational diabetes were excluded. Standard serum lipids, direct LDL-C, sdLDL-C, and apolipoprotein (apo) A-I, A-II, and B, and Lp(a) levels were measured by standard chemical methods, and plasma apolipoproteins and particle numbers were assessed using nuclear magnetic resonance (NMR) methodology. Results were adjusted for gestational age, and smoking, and obtained for preeclampsia compared to normal controls - using general linear models for fixed factor analysis. Log transformations were carried out for non-normally distributed parameters.
In the serum chemistries, significant (p<.05) elevations were found in preeclampsia cases versus controls for direct LDL-C (+10%), small dense LDL-C (+18%), apoB (+10%), and Lp(a) (+50%). Similar alterations were noted in lipoprotein and apolipoprotein analyses by NMR. Results apply in aggregate to all gestational ages.
There are significant serum and plasma lipoprotein and apolipoprotein alterations seen in preeclampsia cases versus control subjects. Increases in atherogenic small dense LDL particles and their constituents have also been associated with increased ASCVD risk in the general population.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Perineural invasion (PNI) is associated with aggressive tumor behavior, recurrence, and metastasis, and can influence the administration of adjuvant treatment. However, standard histopathologic ...examination has limited sensitivity in detecting PNI and does not provide insights into its mechanistic underpinnings.
A multivariate Cox regression was performed to validate associations between PNI and survival in 2,029 patients across 12 cancer types. Differential expression and gene set enrichment analysis were used to learn PNI-associated programs. Machine learning models were applied to build a PNI gene expression classifier. A blinded re-review of hematoxylin and eosin (H&E) slides by a board-certified pathologist helped determine whether the classifier could improve occult histopathologic detection of PNI.
PNI associated with both poor overall survival HR, 1.73; 95% confidence interval (CI), 1.27-2.36;
< 0.001 and disease-free survival (HR, 1.79; 95% CI, 1.38-2.32;
< 0.001). Neural-like, prosurvival, and invasive programs were enriched in PNI-positive tumors (
< 0.001). Although PNI-associated features likely reflect in part the increased presence of nerves, many differentially expressed genes mapped specifically to malignant cells from single-cell atlases. A PNI gene expression classifier was derived using random forest and evaluated as a tool for occult histopathologic detection. On a blinded H&E re-review of sections initially described as PNI negative, more specimens were reannotated as PNI positive in the high classifier score cohort compared with the low-scoring cohort (
= 0.03, Fisher exact test).
This study provides salient biological insights regarding PNI and demonstrates a role for gene expression classifiers to augment detection of histopathologic features.
Abstract
Targeted therapies for molecularly-defined subtypes have led to immense clinical benefit for many cancer types but have generally not been successful for pancreatic cancer. Given that the ...mainstay of treatment remains multi-agent chemotherapy with FOLFIRINOX or gemcitabine/nab-paclitaxel, there remains an urgent need to identify novel actionable vulnerabilities for subsets of PDAC patients. Toward this end, we conducted an integrative, genome-scale examination of genetic dependencies and cell surface targets for PDAC by leveraging CRISPR and RNAi screening data from The Cancer Dependency Map Project, genomic data of bulk patient tumors from The Cancer Genome Atlas, and custom single-nucleus RNA-seq of a 43-patient cohort comprised of untreated and treated specimens. Our results re-affirm the prominence of Ras/MAPK signaling and a synthetically-lethal interaction between VPS4A/B, but also reveal recurrent susceptibilities to genes within the fatty acid metabolism, vesicular transport and exocytosis, and nucleobase synthesis pathways that otherwise have minor to moderate depleting effects on the majority of cell lines. Aberrations in frequent tumor suppressor genes and chromosomal arm-level variations appear to modify the strength of dependencies, including that of KRAS, CCND1, and GPX4, and may serve as predictive biomarkers of response. In addition, we leveraged mRNA profiling of bulk primary tumors as well as metastatic organoid models to conduct a genome-wide search for cell surface targets that are highly-expressed in tumors while lowly or not expressed in other toxicity-prone, non-malignant tissues. These putative drug targets do not need to be cancer dependencies and can be compatible with antibody-based therapeutic strategies that leverage alternative modes of cellular toxicity. Our approach identifies MSLN, NECTIN4, TROP2, and other antigens which have previously been shown to be largely tumor-specific but also reveals the expression of multiple putative targets within the CEACAM, claudin, and tetraspanin families. Finally, molecular subtyping efforts over the past decade have yielded classical and basal-like as consensus subtypes with variations therein, but genetic dependencies and cell surface expression patterns unique to either are insufficiently understood. We identified CLDN18, CEACAM5, and CEACAM6 as cell surface antigens for the classical subtype and MSLN, AQP5, and SLC6A14 for basal-like. Dependency on TLK2 and CCND1 is associated with the basal-like and classical subtype, respectively. Taken together, our integrative genomic approach may provide a precision medicine blueprint for stratifying and targeting pancreatic cancer.
Citation Format: Jimmy A. Guo, Daniel Zhao, Scott P. Ginebaugh, Steven Wang, Ananya D. Jambhale, Patrick Z. Yu, Westley W. Wu, Peter Chen, Maryann Zhao, Kristen E. Lowder, Kevin S. Kapner, Hannah I. Hoffman, Stephanie W. Cheng, Daniel Y. Kim, Rebecca Boiarsky, Francois Aguet, Brenton Paolella, John M. Krill-Burger, James M. McFarland, Tobiloba Oni, Tyler Jacks, Aviv Regev, Gad Getz, William L. Hwang, Harshabad Singh, Andrew J. Aguirre. Integrative genomic characterization of therapeutic targets for pancreatic cancer abstract. In: Proceedings of the AACR Virtual Special Conference on Pancreatic Cancer; 2021 Sep 29-30. Philadelphia (PA): AACR; Cancer Res 2021;81(22 Suppl):Abstract nr PR-006.
Background:
There is limited information about socioeconomic factors effect on survival in veterans with acute myeloid leukemia (AML). Some studies suggested higher risk of leukemia mortality among ...veterans who were smokers 1, 2, 3, 4. Few studies investigated socioeconomic factors like insurance status, care at private or academic center, marital status and median household income effect on outcomes in adults with AML 5, 6, 7.
Methods:
Medical records of AML patients at the Oklahoma City VAHCS between 2010 and 2017 were reviewed. Information collected included home distance from treatment center (≤ 40 miles vs > 40 miles), marital status at diagnosis, tobacco use in the 3 months preceding diagnosis, history of alcohol abuse, level of college education (college education vs less than college education). Fisher-exact test was used for differences in survival rates. Kaplan-Meier analysis was used to estimate the survival and log-rank test to determine differences among groups.
Results:
Total number of Veterans were 28. Fifteen patients (56%) had poor risk disease, 8 (30%) had intermediate risk disease, and 4 (15%) had good risk disease. Median survival for the whole group was 9.3 months. Patients with poor and intermediate risk cytogenetic/molecular status had median survival of 5.5 and 37.7 months, respectively (p=0.0066). There was insufficient number of deaths in the good risk group at the time of this analysis. Median survival for veterans with history of alcohol abuse vs none was 66 vs 7 months (p= 0.15). Median survival for veterans who had some college education vs less than college education was 26.1 vs 6.9, (p=0.14). Median survival for veterans with history of tobacco use within 3 months of diagnosis vs others was 6.9 vs 26.1 (p= 0.11). Median survival for veterans who were married at diagnosis vs non married was 14 vs 7.89 (p=0.29). Median survival for veterans who lived > 40 miles from treatment center vs ≤ 40 miles was 7.43 vs 37.7 months (p=0.5).
Conclusions:
In our retrospective single institute study, poor risk cytogenetic/molecular risk group was associated with inferior survival. While there appeared to be a trend towards worse survival in association with lower education, smoking, non-married status, and longer distance from treatment center, none of these factors had a statistically significant effect. Larger studies are needed to confirm such observations.
References:
1. Austin H, Cole P. Cigarette smoking and leukemia. Journal of chronic diseases. 1986; 39: 417-421.
2. Kahn HA. The Dorn study of smoking and mortality among US veterans: Report on 8.5 years of observation. Bethesda, MD: US Department health, Education and Welfare, 1966; 1-125.
3. Rogot E, Murray JL. Smoking and causes of death among US veterans. 16 years of observation. Public Health Rep. 1980; 95: 213-222.
4. McLaughlin JK, Hrubec Z et al. Cigarette smoking and leukemia. J Natl Cancer Inst 1990; 81: 1262-1263.
5. Luciano Costa, Uma Borate et al. Non Biological factors affecting survival in Younger patients with acute myeloid leukemia. Blood 2014; 124:1273;
6. Gaurav Goyal, Lata Nawal et al. Impact of socioeconomic, demographic and health system factors on therapy in Acute myeloid leukemia. Blood 2015; 126: 3316;
7. Lene Sofie Granfeldt et al, Effects of Education and income on treatment and outcome in patients with AML in tax supported health care system: A national population based cohort study. J Clin Oncol Nov 2017; 35: 3678-3687.
No relevant conflicts of interest to declare.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Abstract
Background: In 2018, cervical cancer (CC) accounted for 311,000 deaths worldwide. Nearly all CC are linked to human papillomavirus (HPV) infection. HPV infection is nearly ubiquitous, but ...persistent infection can lead to dysplasia and ultimately cancer. Cervical dysplasia is classified into low (CIN1), moderate (CIN2), and high (CIN3) cervical intraepithelial neoplasia. CIN2 and CIN3 are considered premalignant lesions, with about 5-12% progressing to CC. However, it is unclear which of these high-risk CIN2/3 patients will go on to develop CC. Chronic HPV infection increases DNA damage and reduces DNA repair. Using a novel, highly sensitive, DNA damage detection assay (q-PADDA) developed in our lab, we have recently shown that nuclear DNA (nDNA) damage is a potential tool to predict oropharyngeal cancer risk, another HPV infection associated malignancy. Herein, we hypothesized that nDNA damage could also be used as a tool to screen for high CC risk.
Aims: (1) To measure the amount of nDNA damage in cervical samples with distinct pathologies. (2) To determine whether the number of DNA lesions correlates with the grade of cervical dysplasia.
Methods: A total of 105 participants were enrolled in the study. Cervical samples were collected using a cytobrush during pelvic examination. Total genomic DNA was extracted, and nDNA damage was quantified using q-PADDA. Demographic, clinicopathologic, and risk factor data were collected from detailed questionnaires and medical charts. Data were subjected to ANOVA and regression analysis using SAS software.
Results: Histopathological analysis revealed that 33 samples had no dysplasia (CIN0), 30 samples were CIN1, 37 samples were CIN2/3, and five samples were CC. DNA damage analysis has been completed in 26 samples. We observed that CIN1 cases had a 2-fold (p<0.05), and CIN2/3 cases had a three-fold (p≤0.02) increase in the number of nDNA lesions when compared to CIN0. No significant correlation was observed between age, race, smoking and alcohol status and final pathology per regression analysis.
Conclusion: Our preliminary analysis reveals that the amount of DNA damage is the lowest in patients without cervical dysplasia and increases progressively with the grade of dysplasia and corresponding CC risk. This promising data supports the use of DNA damage as biomarker of cervical cancer risk. The remainder of this data will be analyzed, but more extensive population studies are warranted to fully assess the potential of this approach to predict CC risk.
Grant support: This work was supported by OSCTR/NIH IDeA Program and The Peggy and Charles Stephenson Cancer Center. Dr. Queimado holds a PHF Endowed Chair in Otorhinolaryngology.
Citation Format: Balaji Sadhasivam, Camille C. Jackson, Katie M. Smith, Tristan Coles, Isha Jhingan, Rebekah Stewart, Elizabeth H. Hahn, Sarah E. Johnston, Daniel Y. Zhao, Vengatesh Ganapathy, Lurdes Queimado. DNA damage level correlates with grade of cervical dysplasia: a potential biomarker to assess cervical cancer risk abstract. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 2547.
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