Single Number Research Articles

Development, validation and application of single molecule molecular inversion probe based novel integrated genetic screening method for 29 common lysosomal storage disorders in India

BackgroundCurrent clinical diagnosis pathway for lysosomal storage disorders (LSDs) involves sequential biochemical enzymatic tests followed by DNA sequencing, which is iterative, has low diagnostic yield and is costly due to overlapping clinical presentations. Here, we describe a novel low-cost and high-throughput sequencing assay using single-molecule molecular inversion probes (smMIPs) to screen for causative single nucleotide variants (SNVs) and copy number variants (CNVs) in genes associated with 29 common LSDs in India.Results903 smMIPs were designed to target exon and exon–intron boundaries of targeted genes (n = 23; 53.7 kb of the human genome) and were equimolarly pooled to create a sequencing library. After extensive validation in a cohort of 50 patients, we screened 300 patients with either biochemical diagnosis (n = 187) or clinical suspicion (n = 113) of LSDs. A diagnostic yield of 83.4% was observed in patients with prior biochemical diagnosis of LSD. Furthermore, diagnostic yield of 73.9% (n = 54/73) was observed in patients with high clinical suspicion of LSD in contrast with 2.4% (n = 1/40) in patients with low clinical suspicion of LSD. In addition to detecting SNVs, the assay could detect single and multi-exon copy number variants with high confidence. Critically, Niemann-Pick disease type C and neuronal ceroid lipofuscinosis-6 diseases for which biochemical testing is unavailable, could be diagnosed using our assay. Lastly, we observed a non-inferior performance of the assay in DNA extracted from dried blood spots in comparison with whole blood.ConclusionWe developed a flexible and scalable assay to reliably detect genetic causes of 29 common LSDs in India. The assay consolidates the detection of multiple variant types in multiple sample types while having improved diagnostic yield at same or lower cost compared to current clinical paradigm.

Insights into Impact: Evaluating an Adult Leadership Program Offered through Michigan State University Extension

Agriculture, food, and natural resource (AFNR) systems need leaders to catalyze positive change. Thus, Extension professionals have consistently developed innovative and impactful leadership programming. In the current study, the alumni of one such program in Michigan were surveyed to evaluate the sustained impact of the program. Program alumni rated themselves highest in Empowerment and Perspective Development and perceived the strongest programmatic impact in Empowerment and Emotional Resilience. These data were further analyzed to create a “Leadership Impact Factor,” which illuminates the impact of a program using a single number. Recommendations are made for Extension professionals facilitating similar leadership education programming.

Modern Approach in Pattern Recognition Using Circular Fermatean Fuzzy Similarity Measure for Decision Making with Practical Applications

The circular Fermatean fuzzy (CFF) set is an advancement of the Fermatean fuzzy (FF) set and the interval-valued Fermatean fuzzy (IVFF) set which deals with uncertainty. The CFF set is represented as a circle of radius ranging from 0 to 2 with the center at the degree of association (DA) and degree of nonassociation (DNA). If multiple people are involved in making decisions, the CFF set, as an alternative to the FF and IVFF sets, can deal with ambiguity more effectively by encircling the decision values within a circle rather than taking an average. Using algorithms, a pattern can be observed computationally or visually. Machine learning algorithm utilizes pattern recognition as an instrument for identifying patterns and also similarity measure (SM) is a beneficial pattern recognition tool used to classify items, discover variations, and make future predictions for decision making. In this work, we introduce the CFF cosine and Dice similarity measures (CFFDMs and CFFSMs), and their properties are studied. Unlike traditional approaches of decision making, which emphasize a single number, the proposed CFFSMs observe the pattern over the circular region to help in dealing with uncertainty more effectively. We introduce an innovative decision-making method in the FF setting. Available bank loans and applicants’ eligibility levels are represented as CFF set using their FF criteria and are taken as loan patterns and customer eligibility patterns. The loan is allocated to the applicant by measuring the CFFCSM and CFFDSM between the two patterns. Also, laptops are suggested to the customers by measuring the similarity between specification pattern and requirement pattern. The correctness and consistency of the proposed models are ensured by comparison analysis and graphical simulations of the input and similarity CFFNs.

U-Plume: automated algorithm for plume detection and source quantification by satellite point-source imagers

Abstract. Current methods for detecting atmospheric plumes and inferring point-source rates from high-resolution satellite imagery are labor-intensive and not scalable with regard to the growing satellite dataset available for methane point sources. Here, we present a two-step algorithm called U-Plume for automated detection and quantification of point sources from satellite imagery. The first step delivers plume detection and delineation (masking) with a U-Net machine learning architecture for image segmentation. The second step quantifies the point-source rate from the masked plume using wind speed information and either a convolutional neural network (CNN) or a physics-based integrated mass enhancement (IME) method. The algorithm can process 62 images (each measuring 128 pixels × 128 pixels) per second on a single 2.6 GHz Intel Core i7-9750H CPU. We train the algorithm using large-eddy simulations of methane plumes superimposed on noisy and variable methane background scenes from the GHGSat-C1 satellite instrument. We introduce the concept of point-source observability, Ops=Q/(UWΔB), as a single dimensionless number to predict plume detectability and source rate quantification error from an instrument as a function of source rate Q, wind speed U, instrument pixel size W, and instrument-dependent background noise ΔB. We show that Ops can powerfully diagnose the ability of an imaging instrument to observe point sources of a certain magnitude under given conditions. U-Plume successfully detects and masks plumes from sources as small as 100 kg h−1 in GHGSat-C1 images over surfaces with low background noise and successfully handles larger point sources over surfaces with substantial background noise. We find that the IME method for source quantification is unbiased over the full range of source rates, while the CNN method is biased towards the mean of its training range. The total error in source rate quantification is dominated by wind speed at low wind speeds and by the masking algorithm at high wind speeds. A wind speed of 2–4 m s−1 is optimal for detection and quantification of point sources from satellite data.

Valuation of Internet of Energy (IoE) Platforms in Smart Cities: A Hybrid Multi-Criteria Decision Making Approach

A smart city is a place where people live using computing, sensing, and networking technology in a variety of ways, including smart buildings, smart homes, smart transportation, smart workplaces, smart offices, smart industries, and smart agriculture. These smart technologies need to connect so; we need to use the Internet of Things (IoT) that has applications in many areas of our smart lives. IoT has been used due to the growing usage of renewable energy sources and the challenges of network management. Internet of Energy (IoE) integrates the IoT and smart grid capabilities. The basic role of smart grids or IoE is an essential element in creating smart cities. In this work, we present some IoE platforms that represent the alternatives and their criteria. The proposed study treats the uncertainty of multi-criteria decision-making (MCDM) modified by single value triangular neutrosophic number (SVTrN) by choosing the optimal IoE platform based on the criteria importance through inter-criteria correlation (CRITIC) method and multi-attributive ideal-real comparative analysis (MAIRCA). The proposed model proved its effectiveness by applying it to an experimental case. The results show that the DCC (A3) platform is the best one.

On democratic string field theories

We reexamine democratic open string field theories, namely, theories in which string fields are not constrained to a single picture number and picture changing is obtained as a gauge transformation. We describe several possibilities for regular free theories and attempt to construct the lowest order interaction term and identify the lowest order gauge transformation for some of these theories. We also discuss projections over string field spaces that might be needed for a consistent off-shell implementation of picture changing.

Abstract PO3-06-05: Association of tumor-derived extracellular vesicles with circulating tumor DNA alterations in metastatic breast cancer patients: exploring differences in inflammatory breast cancer

Abstract Background: Liquid biopsy provides a real-time assessment of metastatic breast cancer (MBC). Recently, the complementary prognostic value of tumor-derived extracellular vesicles (tdEVs) and circulating tumor cells (CTCs) has been reported. We have previously confirmed the strong prognostic significance of CTCs and tdEVs in inflammatory breast cancer (IBC). While previous studies have reported the association of CTCs with circulating tumor DNA (ctDNA) alterations in MBC, no evidence is available for tdEVs. This study aimed to analyze the association of tdEVs with ctDNA alterations, to investigate the molecular pathways underlying their presence. Moreover, we explored potential differences of this association in patients (pts) with IBC to provide a comprehensive liquid biopsy-based portrait of this aggressive subtype of BC. Methods: Blood samples were collected from 355 pts with MBC before starting a new line of therapy at Northwestern University (Chicago, IL) between 2016 and 2021 (NU16B06 trial). For CTCs and tdEVs analysis, 7.5 mL of blood was processed with the CellSearch® system. The ACCEPT software was applied to CellSearch® images to automatically enumerate CTCs and tdEVs. Positivity cutoff was ≥5 for CTCs, while tdEV cutoff points were < 20 (low), 20-79 (intermediate), and ≥80 (high). For ctDNA analysis, matched plasma samples (± 1 month) were analyzed with the Guardant360™ NGS platform for the detection of somatic single nucleotide variants (SNVs) and copy number variations (CNVs), which were classified into oncogenic pathways based on defined profiles generated on the Cancer Genome Atlas database (p53, PI3K, ER, RTK, RAS, RAF, WNT, MYC, cell cycle, notch). Associations between ctDNA pathways alterations and tdEVs were tested in the overall population by multinomial logistic regression and corrected for significant clinical characteristics. Differences in liquid biopsy features between IBC and non-IBC subgroups were analyzed through Fisher's exact test. Results: Of the 355 MBC pts, 210 (62%) had HR+ BC, 61 (17%) had HER2+ BC, and 68 (20%) had triple-negative BC. Eighty-three (23%) had a diagnosis of IBC and had a numerically lower tdEV count. Also, lower tdEVs were detected in HER2+ BC as compared with HR+. Significantly higher tdEVs were observed among pts with lobular histology, liver, and bone metastases. CTC count was significantly associated with tdEV number. A matched plasma sample for ctDNA analysis was available for 175 pts (62 IBC and 113 non-IBC). In the overall population, SNVs in ER pathway were associated with intermediated/high levels of tdEVs (p=0.004 and 0.008). A similar association was observed for CNVs in the cell cycle pathway (p=0.008 and 0.007). Moreover, associations with ≥80 tdEVs were observed for PI3K SNVs and CNVs (p=0.039 and 0.004, respectively), RTK CNVs (p=0.023), and MYC CNVs (p=0.001). In multivariable analysis, clinical characteristics associated with higher tdEVs were lobular histology (p=0.014 for 20-79 and < 0.001 for ≥80) and bone metastases (p=0.019 for 20-79 and 0.002 for ≥80). When considering clinical variables of interest, only ER SNVs and MYC CNVs were significantly associated with intermediate (p=0.031) and high (p=0.022) tdEV counts, respectively. While the association with ER SNVs and cell cycle CNVs was significant both in the IBC and non-IBC subgroups, others were specific for a certain subgroup: higher tdEVs were significantly associated with PI3K SNVs only in non-IBC pts whereas the significant association with CNVs in PI3K and MYC pathways was observed only in pts with IBC. Conclusion: Detection of tdEVs was associated with particular genomic profiles. These alterations seem to be different in IBC further underlying a different biology of this BC subtype. Additional studies are needed to explore how to integrate different liquid-biopsy based biomarkers in the management of pts with MBC. Citation Format: Eleonora Nicolò, Lorenzo Gerratana, Lorenzo Foffano, Laura Munoz Arcos, Mara Serena Serafini, Maroua Manai, Letizia Pontolillo, Nadia Bayou, Elisabetta Molteni, Amanda Kaylan Strickland, Youbin Zhang, Paolo D’Amico, Andrew Davis, Jeannine Donahue, Huiping liu, William Gradishar, Ami Shah, Giuseppe Curigliano, Carolina Reduzzi, Massimo Cristofanilli. Association of tumor-derived extracellular vesicles with circulating tumor DNA alterations in metastatic breast cancer patients: exploring differences in inflammatory breast cancer [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO3-06-05.

Abstract PO2-10-07: Patterns of presentation, treatment and survival for older patients with metastatic breast cancer (MBC): results from a large prospective registry

Abstract Background: The median age of breast cancer diagnosis in the U.S. is 62 years; however, older pts with breast cancer are consistently underrepresented in clinical research. In population-based studies, older pts, particularly those aged 70+, do worse than their younger counterparts at every stage of disease, including stage IV. However, our understanding of patterns of recurrence, treatment patterns, and outcomes for older pts with MBC is limited by a lack of available data. Methods: We identified pts age >60 years seen at least once at a single, NCI-designated cancer center for a diagnosis of MBC between 1999-2022 with 1+ years of follow-up from the time of their metastatic diagnosis. We categorized pts into 5-year age groups (60-65; 66-70; 71-75; 76-80; >80) and two groups of 60-70 and >70. Clinicopathologic characteristics, treatment patterns, reason for treatment discontinuation, and the proportion enrolling on clinical trials were compared by tumor subtype and age group using Chi-Square testing. Median overall survival using Kaplan-Meier method was calculated from the date of initial MBC diagnosis to date of death or last follow-up, examined by tumor subtype and age. Results: The final analytic cohort included 1,115 patients diagnosed with MBC with median follow-up of 2.9 years (1.0-18.5). Median age at MBC diagnosis was 66.3 years (60.0-95.4) and 10% were non-White; disease subtype distribution was the following: 70.7% HR+HER2-, 11.9% HER2+, 17.4% TN. Overall, 22.2 presented with de novo MBC. Presentation of MBC did not vary by ages 60-70 vs. 70+, with no differences in disease characteristics such as grade and disease sites at MBC diagnosis (except for bone). However, the proportion of pts with HR+HER2- disease increased with age, from 69% of MBC in ages 60-70 and 76% in ages >70 (p=.02). In pts with this subtype receiving first-line (1L) therapy (n=783), use of endocrine therapy as 1L (with or without a CDK4/6 inhibitor) increased by age (77.8% in ages 60-65 v. 94.7% in ages >80); use of 1L chemotherapy also varied by age (22.2% in ages 60-65 v. 5.3% in >80). Among pts with HER2+ BC, 89% received a trastuzumab-containing regimen in the 1L setting; in pts with TN MBC, 94% received at least 1L line of chemotherapy. Overall, most pts discontinued 1L therapy for progression, not toxicity, and there was no variation in rates of discontinuation due to toxicity by age with 10.4% noted in both age groups, 60-70 and >70. The proportion of patients receiving 3+ lines of chemotherapy across disease subtype decreased with increasing age (e.g., 54% in ages 60-65 v. 25% in ages >80 among HR+HER2-; 69% in ages 60-65 and 33% in ages >80 among TN MBC). Overall, enrollment on a clinical trial in the MBC setting steadily decreased with older age from 40% in ages 60-65 to 13% in ages >80 (p=.0004). Overall median overall survival differed with increasing age from 4.4 yrs in ages 60-65 to 2.7 yrs in ages >80 (p< 0.005). In descriptive analyses, the proportion of pts alive at 2 yrs was variable. For those ages 60-65, 37.8%, 17.1%, and 42.9% of pts with HR+HER2, TN, and HR-HER2+, respectively were alive at 2 yrs. For those ages >80, 23.7%, 0%, and 0% of pts with HR+HER2-, TN, and, HR-HER2+ disease were alive at 2 yrs. Median survival times were < 2 years for pts with TN regardless of age. Conclusions. In a unique, large prospective cohort of older pts with MBC, we examined detailed information on disease presentation, treatments, and outcomes, lending new information on patterns of care and experiences for older pts with MBC in a modern real-world experience. Limitations include a single center experience and small numbers of older pts with HER2+ and TN disease. Although the oldest pts with MBC had similar disease characteristics as younger pts in our dataset, survival outcomes were poor, particularly for those ages 80+. Therapeutic approaches, likely including improved supportive care, are urgently needed to optimize outcomes in the oldest pts with MBC. Table 1. Outcomes for older pts with MBC Citation Format: Melissa Hughes, Alyssa Patterson, Alexandra Newman, Amanda Higgins, Gregory Kirkner, Janet Files, Molly Skeffington, McKenna Moore, Sarah Strauss, Nicole Kuhnly, Lindsey Crowley, Sara Tolaney, Nancy Lin, Rachel Freedman. Patterns of presentation, treatment and survival for older patients with metastatic breast cancer (MBC): results from a large prospective registry [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO2-10-07.

Zagreb Topological Properties of Hexa Organic Molecular Structures.

In connection with the study of chemical graph theory, it has been explored that a single number can capture the numerical representation of a molecular structure, and this number is known as a topological property (index). This study aimed to explore a few Zagreb topological properties for four hexa organic molecular structures (hexagonal, honeycomb, silicate, and oxide) based on the valency and valency sum of atoms in the structure. We employed the technique of partitioning the set of bonds according to the valency and valency-sum of end atoms of each bond and then performed the computation by using combinatorial rules of counting (that is, the rule of sum and the rule of product). The obtained results were also compared numerically and graphically. Exact values of five valencies based and five valency-sum-based Zagreb topological properties were found for the underline chemical structures.

What Should Healthcare Systems Consider When Modernizing Call Centers? Early Considerations From the Veterans Health Administration.

Growing numbers of hospitals and payers are using call centers to answer patients' clinical and administrative questions, schedule appointments, address billing issues, and offer supplementary care during public health emergencies and national disasters. In 2020, the Veterans Health Administration (VA) implemented VA Health Connect, an enterprise-wide initiative to modernize call centers. VA Health Connect is designed to improve the care experience with the convenience, flexibility, and simplicity of a single toll-free number connected to a range of 24/7 virtual services. The services are organized into four areas: administrative guidance for scheduling and general inquiries; pharmacy support for medication matters; clinical triage for evaluation of symptoms and recommended care; and virtual visits with providers for urgent and episodic care. Through a qualitative evaluation of VA Health Connect, we sought to identify the factors that affected the development of this program and to compile considerations to support the implementation of other enterprise-wide initiatives. The evaluation team interviewed 29 clinical and administrative leads from across the VA. These leads were responsible for the modernization of their local service networks. PhD-level qualitative methodologists conducted the interviews, asking participants to reflect on barriers and facilitators to modernization and implementation. The team employed a rapid qualitative analytic approach commonly used in healthcare research to distill robust results. A review of the early implementation of VA Health Connect found: (1) deadlines proved challenging but provided momentum for the initiative; (2) a balance between standardized processes and local adaptations facilitated implementation; (3) attention to staffing, hiring, and training of call center staff before implementation expedited workflows; (4) establishing national and local leadership commitment to the innovation from the onset increased team cohesion and efficacy; and (5) anticipating information technology infrastructure needs prevented delays to modernization and implementation. Our findings suggest that healthcare systems would benefit from anticipating likely obstacles (e.g., delays in software implementations and negotiations with unions), thus providing ample time to secure leadership buy-in and identify local champions, communicating early and often, and supporting flexible implementation to meet local needs. VA leadership can use this evaluation to refine implementation, and it could also have important implications for regulators, federal health exchanges, insurers, and other healthcare systems when determining resource levels for call centers.

Simplified expressions of uncertainty for single number quantities in ISO 3382-3 (2022).

The ISO 3382-3 (2022) standard defines single number quantities (SNQs) characterizing the spatial decay of speech (D2S, LpAS4m, rC) and of its intelligibility (rD). The standard assesses the accuracy of the measurement using a unique uncertainty value for each SNQ, relying on a round-robin test performed in a single office. To make this assessment more accurate, analytical expressions have been established by applying the law of propagation of uncertainty. These expressions, although precise, are too complex to be included in the standard. This work consists of their simplification, relying on 95 measurements conducted in 36 companies in France and Germany. First, the terms associated with distance measurement uncertainties were found to be negligible. Second, the estimation of the uncertainties of A-weighted speech levels and Speech Transmission Index, based on the measurements made at the workstations constituting the 95 paths, enabled further simplifications. Finally, simplified expressions turn out to be as accurate as the original expressions, and the estimated uncertainties are comparable to those reported by Yadav et al. (2019). If a unique value of uncertainty is to be retained for each SNQ, this study suggests 0.6 dB for D2S and LpAS4m, 7% for rC, and 10% for rD.

Social Media Marketing Tricks and Measuring Impact

Increasing media clutter and changing media habits makes it important to continuously study the advertising effectiveness of each medium. The objective of this study is to analyse and compare the impact of various media ie Television (TV), Radio, Print and Internet on Advertising Effectiveness in terms of its objectives like cognition, affection and conation and also to understand if media context (editorial environment or program context) has any impact on advertising effectiveness. The use of the Return on Marketing Investment (ROMI), is now widespread, and usually considered while evaluating media impact on Advertising Effectiveness. Two types of responses are gathered for this study, namely responses from general respondents and those from the corporate respondents. The corporate responses are mainly gathered from respondents working as senior managers in companies of FMCG products, Durable products and financial services. A simple random sampling technique was used in this study. Sample size was 1000 respondents. Also 50 Senior Managers were surveyed from various companies Standard deviation for every variable is calculated in pilot study data of 115 respondents. Percentages are used for comparison. Further Arithmetic mean is used to consolidate the numeric information in to a single number. Mean scores of variables are obtained using responses given to sub questions of corresponding variables. Standard deviation is used to understand variation in responses given by respondents. Friedman Test is used for non-parametric data as well. Paired t-tests is applied to compare same variable Under two groups. The study revealed that significant difference in effectiveness according to media types whilst there is no significant difference in Media context. Also, there is difference in effectiveness media type and also in Cognitive, Affective and Conative responses according product category (FMCG, Durable, and Financial services). For purchase decision, social media found to be effective. Impact of advertising on revenue of company and significant difference in revenue according to media type was confirmed.

Transition Between Mechanical and Geometric Controls in Glacier Crevassing Processes

AbstractHerein, fast fracture initiation in glacier ice is modeled using a Material Point Method and a simplified constitutive law describing tensile strain softening. Relying on a simple configuration where ice flows over a vertical step, crevasse patterns emerge and are consistent with previous observations reported in the literature. The model’s few parameters allows identification of a single dimensionless number controlling fracture spacing and depth. This scaling law delineates two regimes. In the first one, ice thickness does not play a role and only ice tensile strength controls the spacing, giving rise to numerous surface crevasses, as observed in crevasse fields. In this regime, scaling can recover classical values for ice tensile strength from macroscopic field observations. The second regime, governed by ice bending, produces large‐scale, deep fractures resembling serac falls or calving events.

Genome-wide analysis to uncover how Pocillopora acuta survives the challenging intertidal environment

Characterisation of genomic variation among corals can help uncover variants underlying trait differences and contribute towards genotype prioritisation in coastal restoration projects. For example, there is growing interest in identifying resilient genotypes for transplantation, and to better understand the genetic processes that allow some individuals to survive in specific conditions better than others. The coral species Pocillopora acuta is known to survive in a wide range of habitats, from reefs artificial coastal defences, suggesting its potential use as a starter species for ecological engineering efforts involving coral transplantation onto intertidal seawalls. However, the intertidal section of coastal armour is a challenging environment for corals, with conditions during periods of emersion being particularly stressful. Here, we scanned the entire genome of P. acuta corals to identify the regions harbouring single nucleotide polymorphisms (SNPs) and copy number variations (CNVs) that separate intertidal colonies (n = 18) from those found in subtidal areas (n = 21). Findings revealed 74,391 high quality SNPs distributed across 386 regions of the P. acuta genome. While the majority of the detected SNPs were in non-coding regions, 12% were identified in exons (i.e. coding regions). Functional SNPs that were significantly associated with intertidal colonies were found in overrepresented genomic regions linked to cellular homeostasis, metabolism, and signalling processes, which may represent local environmental adaptation in the intertidal. Interestingly, regions that exhibited CNVs were also associated with metabolic and signalling processes, suggesting P. acuta corals living in the intertidal have a high capacity to perform biological functions critical for survival in extreme environments.

Unintended use of a calculative practice: conflicting institutional logics in the Norwegian fishing industry

PurposeThis paper explores how conflicting institutional logics shape the behaviors of macro- and micro-level actors in their use of a calculative practice. Thereby, this paper explains how quantification can undermine the intended purpose of a governance system based on a single number.Design/methodology/approachThe study draws upon the literature on calculative practices and institutional logics to present the case of how a single number—specifically the conversion factor for Atlantic Cod, established by macro-level actors for the purposes of governance within the Norwegian fishing industry—is interpreted and used by micro-level actors in the industry. The study is based on documents, field observations and interviews with fishers, landing facilities, and control authorities.FindingsThe use of the conversion factor, while intended to protect fish stock and govern industry actions, does not always align with the institutional logics of micro-level actors. Especially during the winter season, these actors may seek to serve their interests, leading to potential system gaming. The reliance on a single number that overlooks seasonal nuances can motivate unintended behaviors, undermining the governance system’s intentions.Originality/valueIntegrating the literature on calculative practices with an institutional logics perspective, this study offers novel insights into the challenges of using quantification for the governance of complex industries. In particular, the paper reveals that when the logics of macro- and micro-level actors conflict in a single-number governance system, unintended outcomes arise due to a domination of the macro-level logics.

Identification and validation of a novel anoikis-related prognostic model for prostate cancer.

Anoikis resistance is a hallmark characteristic of oncogenic transformation, which is crucial for tumor progression and metastasis. The aim of this study was to identify and validate a novel anoikis-related prognostic model for prostate cancer (PCa). We collected a gene expression profile, single nucleotide polymorphism mutation and copy number variation (CNV) data of 495 PCa patients from the TCGA database and 140 PCa samples from the MSKCC dataset. We extracted 434 anoikis-related genes and unsupervised consensus cluster analysis was used to identify molecular subtypes. The immune infiltration, molecular function, and genome alteration of subtypes were evaluated. A risk signature was developed using Cox regression analysis and validated with the MSKCC dataset. We also identify potential drugs for high-risk group patients. Two subtypes were identified. C1 exhibited a higher level of CNV amplification, immune score, stromal score, aneuploidy score, homologous recombination deficiency, intratumor heterogeneity, single-nucleotide variant neoantigens, and tumor mutational burden compared to C2. C2 showed a better survival outcome and had a high level of gamma delta T cell and activated B cell infiltration. The risk signature consisting of four genes (HELLS, ZWINT, ABCC5, and TPSB2) was developed (area under the curve = 0.780) and was found to be an independent prognostic factor for overall survival in PCa patients. Four CTRP-derived and four PRISM-derived compounds were identified for high-risk patients. The anoikis-related prognostic model developed in this study could be a useful tool for clinical decision-making. This study may provide a new perspective for the treatment of anoikis-related PCa.

Malformations of cortical development: Fetal imaging and genetics.

Malformations of cortical development (MCD) are a group of congenital disorders characterized by structural abnormalities in the brain cortex. The clinical manifestations include refractory epilepsy, mental retardation, and cognitive impairment. Genetic factors play a key role in the etiology of MCD. Currently, there is no curative treatment for MCD. Phenotypes such as epilepsy and cerebral palsy cannot be observed in the fetus. Therefore, the diagnosis of MCD is typically based on fetal brain magnetic resonance imaging (MRI), ultrasound, or genetic testing. The recent advances in neuroimaging have enabled the in-utero diagnosis of MCD using fetal ultrasound or MRI. The present study retrospectively reviewed 32 cases of fetal MCD diagnosed by ultrasound or MRI. Then, the chromosome karyotype analysis, single nucleotide polymorphism array or copy number variation sequencing, and whole-exome sequencing (WES) findings were presented. Pathogenic copy number variants (CNVs) or single-nucleotide variants (SNVs) were detected in 22 fetuses (three pathogenic CNVs [9.4%, 3/32] and 19 SNVs [59.4%, 19/32]), corresponding to a total detection rate of 68.8% (22/32). The results suggest that genetic testing, especially WES, should be performed for fetal MCD, in order to evaluate the outcomes and prognosis, and predict the risk of recurrence in future pregnancies.

Probing transverse momentum dependent structures with azimuthal dependence of energy correlators

We study the azimuthal angle dependence of the energy-energy correlators \\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\langle \\mathcal{E}\\left({\\widehat{n}}_{1}\\right)\\mathcal{E}\\left({\\widehat{n}}_{2}\\right)\\rangle $$\\end{document} in the back-to-back region for e+e− annihilation and deep inelastic scattering (DIS) processes with general polarization of the proton beam. We demonstrate that the polarization information of the beam and the underlying partons from the hard scattering is propagated into the azimuthal angle dependence of the energy-energy correlators. In the process, we define the Collins-type EEC jet functions and introduce a new EEC observable using the lab-frame angles in the DIS process. Furthermore, we extend our formalism to explore the two-point energy correlation between hadrons with different quantum numbers \\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$${\\mathbb{S}}_{i}$$\\end{document} in the back-to-back limit \\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\langle {\\mathcal{E}}_{{\\mathbb{S}}_{1}}\\left({\\widehat{n}}_{1}\\right){\\mathcal{E}}_{{\\mathbb{S}}_{2}}\\left({\\widehat{n}}_{2}\\right)\\rangle $$\\end{document}. We find that in the Operator Product Expansion (OPE) region the nonperturbative information is entirely encapsulated by a single number. Using our formalism, we present several phenomenological studies that showcase how energy correlators can be used to probe transverse momentum dependent structures.

A Theory of Best Choice Selection through Objective Arguments Grounded in Linear Response Theory Concepts

In this study, we propose how to use objective arguments grounded in statistical mechanics concepts in order to obtain a single number, obtained after aggregation, which would allow for the ranking of “agents”, “opinions”, etc., all defined in a very broad sense. We aim toward any process which should a priori demand or lead to some consensus in order to attain the presumably best choice among many possibilities. In order to specify the framework, we discuss previous attempts, recalling trivial means of scores—weighted or not—Condorcet paradox, TOPSIS (Technique for Order Preference by Similarity to Ideal Solution), etc. We demonstrate, through geometrical arguments on a toy example and with four criteria, that the pre-selected order of criteria in previous attempts makes a difference in the final result. However, it might be unjustified. Thus, we base our “best choice theory” on the linear response theory in statistical physics: we indicate that one should be calculating correlations functions between all possible choice evaluations, thereby avoiding an arbitrarily ordered set of criteria. We justify the point through an example with six possible criteria. Applications in many fields are suggested. Furthermore, two toy models, serving as practical examples and illustrative arguments are discussed.

Automated mood disorder symptoms monitoring from multivariate time-series sensory data: getting the full picture beyond a single number

Mood disorders (MDs) are among the leading causes of disease burden worldwide. Limited specialized care availability remains a major bottleneck thus hindering pre-emptive interventions. MDs manifest with changes in mood, sleep, and motor activity, observable in ecological physiological recordings thanks to recent advances in wearable technology. Therefore, near-continuous and passive collection of physiological data from wearables in daily life, analyzable with machine learning (ML), could mitigate this problem, bringing MDs monitoring outside the clinician’s office. Previous works predict a single label, either the disease state or a psychometric scale total score. However, clinical practice suggests that the same label may underlie different symptom profiles, requiring specific treatments. Here we bridge this gap by proposing a new task: inferring all items in HDRS and YMRS, the two most widely used standardized scales for assessing MDs symptoms, using physiological data from wearables. To that end, we develop a deep learning pipeline to score the symptoms of a large cohort of MD patients and show that agreement between predictions and assessments by an expert clinician is clinically significant (quadratic Cohen’s κ and macro-average F1 score both of 0.609). While doing so, we investigate several solutions to the ML challenges associated with this task, including multi-task learning, class imbalance, ordinal target variables, and subject-invariant representations. Lastly, we illustrate the importance of testing on out-of-distribution samples.