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Article ; Online: Gigaohm and Teraohm Resistors in Femtoamp and Picoamp Electrospray Ionization.

Allen, Nicholas / Li, Huishan / Wang, Taoqing / Li, Anyin

Journal of the American Society for Mass Spectrometry

2023 Volume 34, Issue 5, Page(s) 913–921

Abstract: The femtoamp electrospray ionization (femtoESI) mode has been shown to exhibit unique characteristics that may facilitate ionization efficiency studies and experiments requiring low ion beam flux. Investigation of femtoESI was hindered by a tiny, applied ...

Abstract	The femtoamp electrospray ionization (femtoESI) mode has been shown to exhibit unique characteristics that may facilitate ionization efficiency studies and experiments requiring low ion beam flux. Investigation of femtoESI was hindered by a tiny, applied voltage window of 10-100 V, beyond which ionization currents quickly jumped to nanoamps. This window was difficult to locate because the exact onset voltage fluctuates due to variations in ion source alignments. Large resistors (0.1-100 TΩ) in series effectively expanded the femtoESI applied voltage range, up to 1400 V. By swapping resistors, rapid alternation allows for the comparison of both ESI modes under the same alignment. In peptide mixtures, analytes with lower surface activity are suppressed in the nanoESI mode whereas the femtoESI mode shows signal enhancement of less surface-active species. For protein solutions, there is little change in the charge states generated but the femtoESI mode does show a decrease in the average charge state of protein peaks. Peptides and proteins analyzed in the femtoESI mode also tend to generate higher intensity sodiated peaks over protonated peaks at specific charge states compared with nanoESI mode operation.
Language	English
Publishing date	2023-04-13
Publishing country	United States
Document type	Journal Article
ZDB-ID	1073671-2
ISSN	1879-1123 ; 1044-0305
ISSN (online)	1879-1123
ISSN	1044-0305
DOI	10.1021/jasms.2c00369
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Zs.A 4618: Show issues			Location: Je nach Verfügbarkeit (siehe Angabe bei Bestand) bis Jg. 1994: Bestellungen von Artikeln über das Online-Bestellformular Jg. 1995 - 2021: Lesesall (2.OG) ab Jg. 2022: Lesesaal (EG)
Zs.MO 241: Show issues

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Article ; Online: Supervised convex clustering.

Wang, Minjie / Yao, Tianyi / Allen, Genevera I

Biometrics

2023 Volume 79, Issue 4, Page(s) 3846–3858

Abstract: Clustering has long been a popular unsupervised learning approach to identify groups of similar objects and discover patterns from unlabeled data in many applications. Yet, coming up with meaningful interpretations of the estimated clusters has often ... ...

Abstract	Clustering has long been a popular unsupervised learning approach to identify groups of similar objects and discover patterns from unlabeled data in many applications. Yet, coming up with meaningful interpretations of the estimated clusters has often been challenging precisely due to their unsupervised nature. Meanwhile, in many real-world scenarios, there are some noisy supervising auxiliary variables, for instance, subjective diagnostic opinions, that are related to the observed heterogeneity of the unlabeled data. By leveraging information from both supervising auxiliary variables and unlabeled data, we seek to uncover more scientifically interpretable group structures that may be hidden by completely unsupervised analyses. In this work, we propose and develop a new statistical pattern discovery method named supervised convex clustering (SCC) that borrows strength from both information sources and guides towards finding more interpretable patterns via a joint convex fusion penalty. We develop several extensions of SCC to integrate different types of supervising auxiliary variables, to adjust for additional covariates, and to find biclusters. We demonstrate the practical advantages of SCC through simulations and a case study on Alzheimer's disease genomics. Specifically, we discover new candidate genes as well as new subtypes of Alzheimer's disease that can potentially lead to better understanding of the underlying genetic mechanisms responsible for the observed heterogeneity of cognitive decline in older adults.
MeSH term(s)	Humans ; Aged ; Alzheimer Disease/genetics ; Genomics ; Cluster Analysis
Language	English
Publishing date	2023-04-12
Publishing country	United States
Document type	Journal Article ; Research Support, U.S. Gov't, Non-P.H.S. ; Research Support, N.I.H., Extramural
ZDB-ID	213543-7
ISSN	1541-0420 ; 0099-4987 ; 0006-341X
ISSN (online)	1541-0420
ISSN	0099-4987 ; 0006-341X
DOI	10.1111/biom.13860
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Zs.B 72: Show issues

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Article ; Online: Patterns of health care interactions of individuals with alcohol use disorder: A latent class analysis.

Phillips, Aryn Z / Wang, Yaojie / Allen, Norrina B

Journal of substance use and addiction treatment

2023 Volume 159, Page(s) 209251

Abstract: Introduction: Given the high rates at which individuals with alcohol use disorder (AUD) utilize health care for co-existing conditions, health systems are promising venues for interventions that will facilitate access to AUD treatment. However, how ... ...

Abstract	Introduction: Given the high rates at which individuals with alcohol use disorder (AUD) utilize health care for co-existing conditions, health systems are promising venues for interventions that will facilitate access to AUD treatment. However, how individuals with AUD interact with such systems and, thus, how systems should intervene is unclear. In this study, we seek to identify patterns in how individuals diagnosed with AUD within an academic health system interacted with the system prior to diagnosis. Methods: We use electronic health records from a single academic health system in a major US metropolitan area to create a deidentified retrospective cohort including all individuals age 18+ diagnosed with AUD 2010-2019 (n = 26,899). Latent class analysis (LCA) identified subgroups defined by aspects of previous system interaction and health status, including having an in-system primary care provider, previous utilization of primary and specialty care, diagnosis setting, payer, and presence of other chronic conditions. We then assessed subgroup differences in demographics and associations with in-system AUD treatment receipt in the year following diagnosis, adjusting for demographics. Results: The population was on average 38.6 years old (standard deviation = 15.4) and predominantly male (66.1 %), White (64.5 %), and not of Hispanic/Latino ethnicity (87.8 %). Only 4.7 % received in-system treatment following diagnosis. We deemed the four-class model the optimal LCA model. This model identified subgroups that can be described as 1) average utilization (20.7 % of population), 2) low utilization (54.5 %), 3) high health burden and low utilization (14.2 %), and 4) high health burden and high utilization (10.6 %). Predicted membership in the high health burden and high utilization subgroup and low utilization subgroup were associated with higher and lower odds of treatment receipt, respectively, compared with predicted membership in the average utilization subgroup (odds ratio (OR) for high/high subgroup = 1.21, 95 % confidence interval (CI) = 1.01, 1.27; OR for low subgroup = 0.29 95 % CI = 0.24, 0.34). Conclusion: Individuals diagnosed with AUD within a health system interact with that system in markedly different ways and are unlikely to benefit uniformly from system-based interventions to facilitate treatment. Group-tailored interventions are more likely to have impact and provide returns on investments for systems.
MeSH term(s)	Humans ; Male ; Adolescent ; Adult ; Female ; Alcoholism/diagnosis ; Retrospective Studies ; Latent Class Analysis ; Ethnicity ; Delivery of Health Care
Language	English
Publishing date	2023-12-10
Publishing country	United States
Document type	Journal Article
ISSN	2949-8759
ISSN (online)	2949-8759
DOI	10.1016/j.josat.2023.209251
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Article: Integrative Generalized Convex Clustering Optimization and Feature Selection for Mixed Multi-View Data.

Wang, Minjie / Allen, Genevera I

Journal of machine learning research : JMLR

2021 Volume 22

Abstract: In mixed multi-view data, multiple sets of diverse features are measured on the same set of samples. By integrating all available data sources, we seek to discover common group structure among the samples that may be hidden in individualistic cluster ... ...

Abstract	In mixed multi-view data, multiple sets of diverse features are measured on the same set of samples. By integrating all available data sources, we seek to discover common group structure among the samples that may be hidden in individualistic cluster analyses of a single data view. While several techniques for such integrative clustering have been explored, we propose and develop a convex formalization that enjoys strong empirical performance and inherits the mathematical properties of increasingly popular convex clustering methods. Specifically, our Integrative Generalized Convex Clustering Optimization (iGecco) method employs different convex distances, losses, or divergences for each of the different data views with a joint convex fusion penalty that leads to common groups. Additionally, integrating mixed multi-view data is often challenging when each data source is high-dimensional. To perform feature selection in such scenarios, we develop an adaptive shifted group-lasso penalty that selects features by shrinking them towards their loss-specific centers. Our so-called iGecco+ approach selects features from each data view that are best for determining the groups, often leading to improved integrative clustering. To solve our problem, we develop a new type of generalized multi-block ADMM algorithm using sub-problem approximations that more efficiently fits our model for big data sets. Through a series of numerical experiments and real data examples on text mining and genomics, we show that iGecco+ achieves superior empirical performance for high-dimensional mixed multi-view data.
Language	English
Publishing date	2021-11-06
Publishing country	United States
Document type	Journal Article
ZDB-ID	2042762-1
ISSN	1533-7928 ; 1532-4435
ISSN (online)	1533-7928
ISSN	1532-4435
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Article ; Online: Stochastic models of infectious diseases in a periodic environment with application to cholera epidemics.

Allen, Linda J S / Wang, Xueying

Journal of mathematical biology

2021 Volume 82, Issue 6, Page(s) 48

Abstract: Seasonal variation affects the dynamics of many infectious diseases including influenza, cholera and malaria. The time when infectious individuals are first introduced into a population is crucial in predicting whether a major disease outbreak occurs. In ...

Abstract	Seasonal variation affects the dynamics of many infectious diseases including influenza, cholera and malaria. The time when infectious individuals are first introduced into a population is crucial in predicting whether a major disease outbreak occurs. In this investigation, we apply a time-nonhomogeneous stochastic process for a cholera epidemic with seasonal periodicity and a multitype branching process approximation to obtain an analytical estimate for the probability of an outbreak. In particular, an analytic estimate of the probability of disease extinction is shown to satisfy a system of ordinary differential equations which follows from the backward Kolmogorov differential equation. An explicit expression for the mean (resp. variance) of the first extinction time given an extinction occurs is derived based on the analytic estimate for the extinction probability. Our results indicate that the probability of a disease outbreak, and mean and standard derivation of the first time to disease extinction are periodic in time and depend on the time when the infectious individuals or free-living pathogens are introduced. Numerical simulations are then carried out to validate the analytical predictions using two examples of the general cholera model. At the end, the developed theoretical results are extended to more general models of infectious diseases.
MeSH term(s)	Cholera ; Communicable Diseases/epidemiology ; Epidemics ; Humans ; Models, Biological ; Stochastic Processes
Language	English
Publishing date	2021-04-08
Publishing country	Germany
Document type	Journal Article
ZDB-ID	187101-8
ISSN	1432-1416 ; 0303-6812
ISSN (online)	1432-1416
ISSN	0303-6812
DOI	10.1007/s00285-021-01603-4
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Zs.A 1495: Show issues

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Article: Astrocyte CCN1 stabilizes neural circuits in the adult brain.

Sancho, Laura / Boisvert, Matthew M / Dawoodtabar, Trinity / Burgado, Jillybeth / Wang, Ellen / Allen, Nicola J

bioRxiv : the preprint server for biology

2024

Abstract: Neural circuits in many brain regions are refined by experience. Sensory circuits support higher plasticity at younger ages during critical periods - times of circuit refinement and maturation - and limit plasticity in adulthood for circuit stability. ... ...

Abstract	Neural circuits in many brain regions are refined by experience. Sensory circuits support higher plasticity at younger ages during critical periods - times of circuit refinement and maturation - and limit plasticity in adulthood for circuit stability. The mechanisms underlying these differing plasticity levels and how they serve to maintain and stabilize the properties of sensory circuits remain largely unclear. By combining a transcriptomic approach with
Language	English
Publishing date	2024-03-14
Publishing country	United States
Document type	Preprint
DOI	10.1101/2024.03.14.585077
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Article ; Online: Core features of callous-unemotional traits: a cross-cultural comparison of youth in four countries.

Deng, Jiaxin / Shou, Yiyun / Wang, Meng-Cheng / Allen, Jennifer L / Gao, Yu / Hawes, David J

European child & adolescent psychiatry

2024

Abstract: With considerable debate concerning the impact of culture on the expression of callous-unemotional (CU) traits, it is unclear whether the core features of CU traits generalize to youth across cultures. This study aimed to examine whether cultural ... ...

Abstract	With considerable debate concerning the impact of culture on the expression of callous-unemotional (CU) traits, it is unclear whether the core features of CU traits generalize to youth across cultures. This study aimed to examine whether cultural differences are reflected in the core features of CU traits and the associations among these features. Network analysis was employed to identify the core features and to examine the network structure of CU traits operationalized by the Inventory of Callous Unemotional traits (ICU) in four community youth samples from different nations (Australia, N = 190; the UK, N = 437; the USA, N = 330; China, N = 503). The item "Apologizes to people" was identified as a cross-cultural core feature in the ICU network with a greater centrality of this item compared to others in all four samples. In addition, some items were identified as culture-specific core features in the network, differing in their centrality across samples. The network structures of the youth self-report ICU items were moderately similar across samples, while the structures of parent-report items showed substantial differences. These findings have important implications for cross-cultural research on CU traits as well as practical implications for screening and treatment. The core features of ICU appear to be generalizable in youth across cultures, although cultural-specific manifestations should be noted.
Language	English
Publishing date	2024-01-05
Publishing country	Germany
Document type	Journal Article
ZDB-ID	1118299-4
ISSN	1435-165X ; 1018-8827 ; 1433-5719
ISSN (online)	1435-165X
ISSN	1018-8827 ; 1433-5719
DOI	10.1007/s00787-023-02357-8
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Zs.A 3524: Show issues

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Article ; Online: Feasibility of Omitting Sentinel Lymph Node Biopsy in an Under-screened Cohort of Breast Cancer Patients With a Premastectomy Diagnosis of Ductal Carcinoma In Situ.

Pang, Jinnie / Yan, Zhiyan / Tan, Qing Ting / Allen, John C / Wang, Mingjia / Lim, Geok Hoon

Clinical breast cancer

2024

Abstract: Background: Nodal involvement in ductal carcinoma in situ (DCIS) is rare. In patients with DCIS diagnosis prior to mastectomy, a sentinel lymph node biopsy (SLNB) is usually performed during mastectomy, to avoid the risk of reoperation and the non- ... ...

Abstract	Background: Nodal involvement in ductal carcinoma in situ (DCIS) is rare. In patients with DCIS diagnosis prior to mastectomy, a sentinel lymph node biopsy (SLNB) is usually performed during mastectomy, to avoid the risk of reoperation and the non-identification of SLN subsequently, should there be an upgrade to invasive cancer. We aimed to study the feasibility of omitting SLNB in an under-screened cohort, with mostly symptomatic patients and DCIS diagnosis before mastectomy, by determining the upgrade rate to invasive cancer/ DCIS microinvasion (DCISM) and its associated risk factors. Methods: Patients with pure DCIS diagnosis premastectomy were reviewed retrospectively. Patients with known DCISM or invasive cancer before mastectomy and bilateral cancers were excluded. Patients' demographics, radiological and pathological data premastectomy were analyzed. Results: A total of 189 patients were included. The mean age was 53.8 (range: 29-85) years old. About 64.4% presented with symptoms. 36.0% and 15.3% upgraded to invasive cancer and DCISM on mastectomy respectively. Palpable tumor (P = .0036), large size on ultrasound (P = .0283), tumor seen on mammogram and ultrasound (P = .0082), ultrasound-guided biopsy (P < .0001), high-grade DCIS on biopsy (P = .0350) and no open biopsy/lumpectomy before mastectomy (P < .0001) were associated with the upgrade, with the latter factor remaining significant after multivariable analysis. Nodal involvement was 8.47% and was associated with invasive cancer (P < .0001). Conclusion: In a cohort who had DCIS diagnosis before mastectomy and were mostly symptomatic, the upgrade rate was 51.3%. Despite the high upgrade rate, nodal involvement remained comparable. Risk factors could select patients for omission of upfront SLNB, with a delayed SLNB planned if needed.
Language	English
Publishing date	2024-02-05
Publishing country	United States
Document type	Journal Article
ZDB-ID	2106734-X
ISSN	1938-0666 ; 1526-8209
ISSN (online)	1938-0666
ISSN	1526-8209
DOI	10.1016/j.clbc.2024.02.002
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Zs.A 5800: Show issues			Location: Je nach Verfügbarkeit (siehe Angabe bei Bestand) bis Jg. 1994: Bestellungen von Artikeln über das Online-Bestellformular Jg. 1995 - 2021: Lesesall (2.OG) ab Jg. 2022: Lesesaal (EG)
Zs.MO 498: Show issues

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Article ; Online: Orphan GPR52 as an emerging neurotherapeutic target.

Ali, Saghir / Wang, Pingyuan / Murphy, Ryan E / Allen, John A / Zhou, Jia

Drug discovery today

2024 Volume 29, Issue 4, Page(s) 103922

Abstract: GPR52 is a highly conserved, brain-enriched, ... ...

Abstract	GPR52 is a highly conserved, brain-enriched, G
MeSH term(s)	Humans ; Receptors, G-Protein-Coupled/metabolism ; Brain/metabolism ; Huntington Disease/drug therapy ; Drug Discovery
Chemical Substances	Receptors, G-Protein-Coupled ; GPR52 protein, human
Language	English
Publishing date	2024-02-20
Publishing country	England
Document type	Journal Article ; Review
ZDB-ID	1324988-5
ISSN	1878-5832 ; 1359-6446
ISSN (online)	1878-5832
ISSN	1359-6446
DOI	10.1016/j.drudis.2024.103922
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Zs.A 4725: Show issues

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Article: Functionally selective dopamine D1 receptor endocytosis and signaling by catechol and non-catechol agonists.

Nilson, Ashley N / Felsing, Daniel E / Wang, Pingyuan / Jain, Manish / Zhou, Jia / Allen, John

bioRxiv : the preprint server for biology

2024

Abstract: The dopamine D1 receptor (D1R) has fundamental roles in voluntary movement and memory and is a validated drug target for neurodegenerative and neuropsychiatric disorders. However, previously developed D1R selective agonists possess a catechol moiety ... ...

Abstract	The dopamine D1 receptor (D1R) has fundamental roles in voluntary movement and memory and is a validated drug target for neurodegenerative and neuropsychiatric disorders. However, previously developed D1R selective agonists possess a catechol moiety which displays poor pharmacokinetic properties. The first selective non-catechol D1R agonists were recently discovered and unexpectedly many of these ligands showed G protein biased signaling. Here, we investigate both catechol and non-catechol D1R agonists to validate potential biased signaling and examine if this impacts agonist-induced D1R endocytosis. We determined that most, but not all, non-catechol agonists display G protein biased signaling at the D1R and have reduced or absent Beta-arrestin recruitment. A notable exception was compound (Cmpd) 19, a non-catechol agonist with full efficacy at both D1R-G protein or D1R Beta-arrestin pathways. In addition, the catechol ligand A-77636 was a highly potent, super agonist for D1R Beta-arrestin activity. When examined for agonist-induced D1R endocytosis, balanced agonists SKF-81297 and Cmpd 19 induced robust D1R endocytosis while the G protein biased agonists did not. The Beta-arrestin super agonist, A-77636, showed significantly increased D1R endocytosis. Moreover, Beta-arrestin recruitment efficacy of tested agonists strongly correlated with total D1R endocytosis. Taken together, these results indicate the degree of D1R signaling functional selectivity profoundly impacts D1R endocytosis regardless of pharmacophore. The range of functional selectivity of these D1R agonists will provide valuable tools to further investigate D1R signaling, trafficking and therapeutic potential.
Language	English
Publishing date	2024-04-17
Publishing country	United States
Document type	Preprint
DOI	10.1101/2024.04.15.589637
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