Verifying Fairness in Quantum Machine Learning

Due to the beyond-classical capability of quantum computing, quantum machine learning is applied independently or embedded in classical models for decision making, especially in the field of finance. Fairness and other ethical issues are often one of the main concerns in decision making. In this work, we define a formal framework for the fairness verification and analysis of quantum machine learning decision models, where we adopt one of the most popular notions of fairness in the literature based on the intuition -- any two similar individuals must be treated similarly and are thus unbiased. We show that quantum noise can improve fairness and develop an algorithm to check whether a (noisy) quantum machine learning model is fair. In particular, this algorithm can find bias kernels of quantum data (encoding individuals) during checking. These bias kernels generate infinitely many bias pairs for investigating the unfairness of the model. Our algorithm is designed based on a highly efficient data structure -- Tensor Networks -- and implemented on Google's TensorFlow Quantum. The utility and effectiveness of our algorithm are confirmed by the experimental results, including income prediction and credit scoring on real-world data, for a class of random (noisy) quantum decision models with 27 qubits ($2^{27}$-dimensional state space) tripling ($2^{18}$ times more than) that of the state-of-the-art algorithms for verifying quantum machine learning models

Detecting Violations of Differential Privacy for Quantum Algorithms

Quantum algorithms for solving a wide range of practical problems have been proposed in the last ten years, such as data search and analysis, product recommendation, and credit scoring. The concern about privacy and other ethical issues in quantum computing naturally rises up. In this paper, we define a formal framework for detecting violations of differential privacy for quantum algorithms. A detection algorithm is developed to verify whether a (noisy) quantum algorithm is differentially private and automatically generate bugging information when the violation of differential privacy is reported. The information consists of a pair of quantum states that violate the privacy, to illustrate the cause of the violation. Our algorithm is equipped with Tensor Networks, a highly efficient data structure, and executed both on TensorFlow Quantum and TorchQuantum which are the quantum extensions of famous machine learning platforms -- TensorFlow and PyTorch, respectively. The effectiveness and efficiency of our algorithm are confirmed by the experimental results of almost all types of quantum algorithms already implemented on realistic quantum computers, including quantum supremacy algorithms (beyond the capability of classical algorithms), quantum machine learning models, quantum approximate optimization algorithms, and variational quantum eigensolvers with up to 21 quantum bits

An organogenesis network-based comparative transcriptome analysis for understanding early human development in vivo and in vitro

<p>Abstract</p> <p>Background</p> <p>Integrated networks hold great promise in a variety of contexts. In a recent study, we have combined expression and interaction data to identify a putative network underlying early human organogenesis that contains two modules, the stemness-relevant module (hStemModule) and the differentiation-relevant module (hDiffModule). However, owing to its hypothetical nature, it remains unclear whether this network allows for comparative transcriptome analysis to advance our understanding of early human development, both <it>in vivo </it>and <it>in vitro</it>.</p> <p>Results</p> <p>Based on this integrated network, we here report comparisons with the context-dependent transcriptome data from a variety of sources. By viewing the network and its two modules as gene sets and conducting gene set enrichment analysis, we demonstrate the network's utility as a quantitative monitor of the stem potential <it>versus </it>the differentiation potential. During early human organogenesis, the hStemModule reflects the generality of a gradual loss of the stem potential. The hDiffModule indicates the stage-specific differentiation potential and is therefore not suitable for depicting an extended developmental window. Processing of cultured cells of different types further revealed that the hStemModule is a general indicator that distinguishes different cell types in terms of their stem potential. In contrast, the hDiffModule cannot distinguish between differentiated cells of different types but is able to predict differences in the differentiation potential of pluripotent cells of different origins. We also observed a significant positive correlation between each of these two modules and early embryoid bodies (EBs), which are used as <it>in vitro </it>differentiation models. Despite this, the network-oriented comparisons showed considerable differences between the developing embryos and the EBs that were cultured <it>in vitro </it>over time to try to mimic <it>in vivo </it>processes.</p> <p>Conclusions</p> <p>We strongly recommend the use of these two modules either when pluripotent cell types of different origins are involved or when the comparisons made are constrained to the in <it>vivo </it>embryos during early human organogenesis (and an equivalent <it>in vitro </it>differentiation models). Network-based comparative transcriptome analysis will contribute to an increase in knowledge about human embryogenesis, particularly when only transcriptome data are currently available. These advances will add an extra dimension to network applications.</p

Giα proteins exhibit functional differences in the activation of ERK1/2, Akt and mTORC1 by growth factors in normal and breast cancer cells

Background In a classic model, Giα proteins including Gi1α, Gi2α and Gi3α are important for transducing signals from Giα protein-coupled receptors (GiαPCRs) to their downstream cascades in response to hormones and neurotransmitters. Our previous study has suggested that Gi1α, Gi2α and Gi3α are also important for the activation of the PI3K/Akt/mTORC1 pathway by epidermal growth factor (EGF) and its family members. However, a genetic role of these Giα proteins in the activation of extracellular signal-regulated protein kinase 1 and 2 (ERK1/2) by EGF is largely unknown. Further, it is not clear whether these Giα proteins are also engaged in the activation of both the Akt/mTORC1 and ERK1/2 pathways by other growth factor family members. Additionally, a role of these Giα proteins in breast cancer remains to be elucidated. Results We found that Gi1/3 deficient MEFs with the low expression level of Gi2α showed defective ERK1/2 activation by EGFs, IGF-1 and insulin, and Akt and mTORC1 activation by EGFs and FGFs. Gi1/2/3 knockdown breast cancer cells exhibited a similar defect in the activations and a defect in in vitro growth and invasion. The Giα proteins associated with RTKs, Gab1, FRS2 and Shp2 in breast cancer cells and their ablation impaired Gab1’s interactions with Shp2 in response to EGF and IGF-1, or with FRS2 and Grb2 in response to bFGF. Conclusions Giα proteins differentially regulate the activation of Akt, mTORC1 and ERK1/2 by different families of growth factors. Giα proteins are important for breast cancer cell growth and invasion.Fil: Wang, Zhanwei. University of Hawaii Cancer Center. Honolulu; Estados UnidosFil: Dela Cruz, Rica. University of Hawaii Cancer Center. Honolulu; Estados UnidosFil: Ji, Fang. Shanghai Jiao Tong University . Sahnghai; ChinaFil: Guo, Sheng. University of Hawaii Cancer Center. Honolulu; Estados Unidos. Shanghai Jiaotong University. Shangha; Estados UnidosFil: Zhang, Jianhua. Shanghai Jiaotong University. Shangha; Estados Unidos. University of Hawaii Cancer Center. Honolulu; Estados UnidosFil: Wang, Ying. David Geffen School of Medicine at UCLA. Los Angeles; Estados UnidosFil: Feng, Gen-Sheng. University of California at San Diego; Estados UnidosFil: Birnbaumer, Lutz. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. National Institutes of Health; Estados UnidosFil: Jiang, Meisheng. David Geffen School of Medicine at UCLA. Los Angeles; Estados UnidosFil: Chu, Wen Ming. University of Hawaii Cancer Center. Honolulu; Estados Unido

Independent markers of nonalcoholic fatty liver disease in a gentrifying population‐based Chinese cohort

BackgroundPrevalence of nonalcoholic fatty liver disease (NAFLD) is increasing in developing countries, but its causes are not known. We aimed to ascertain the prevalence and determinants of NAFLD in a new largely unmedicated population‐based cohort from the rapidly gentrifying region of Pinggu, China.MethodsWe randomized cluster sampled 4002 Pinggu residents aged 26 to 76 years. Data from 1238 men and 1928 women without significant alcohol drinking or hepatitis virus B or C infection were analysed. NAFLD was defined using a liver‐spleen ratio (L/S ratio) ≤1.1 on unenhanced abdominal computed tomography (CT) scanning.ResultsOf men and women, 26.5% and 20.1%, respectively, had NAFLD. NAFLD prevalence was highest in younger men and older women. In multivariate logistic regression models, higher body mass index, waist circumference, serum triglyceride, alanine transaminase, and haemoglobin A1c independently increased the odds of NAFLD in both men and women separately. Higher annual household income and systolic blood pressure for men and higher serum uric acid and red meat intake and lower physical activity levels for women also independently associated with higher odds of NAFLD. Individuals with L/S ratio ≤1.1 had linearly increasing rates of obesity, diabetes, and metabolic syndrome that paralleled fatty liver increase.ConclusionsNAFLD is common in a gentrifying Chinese population particularly in younger men of high socioeconomic status and older women with sedentary behaviour who eat red meat. Demographic factors add independent risk of NAFLD above traditional metabolic risk factors. A CT L/S ratio of ≤1.1 identifies individuals at high risk of metabolic disease.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/149708/1/dmrr3156_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/149708/2/dmrr3156.pd

2-Chloro­ethyl 2-(2-chloro­phen­yl)-2-(4,5,6,7-tetrahydro­thieno[3,2-c]pyridin-5-yl)acetate

The mol­ecular packing of the title compound, C17H17Cl2NO2S, is stabilized by weak C—H⋯O and C—H⋯Cl inter­actions. The ester chain is almost planar with a mean deviation of 0.0605 Å and makes dihedral angles of 71.60 (4) and 74.70 (8)° with the benzene ring and the thio­phene ring, respectively. The benzene and thio­phene rings make a dihedral angle of 84.22 (7)°

3-Bromo­propyl 2-(2-chloro­phen­yl)-2-(4,5,6,7-tetra­hydro­thieno[3,2-c]pyridin-5-yl)acetate

In the crystal structure of the title compound, C18H19BrClNO2S, weak C—H⋯O inter­actions help to establish the packing

Model dostosowywania dawki i analiza czynnika współzależnego u chińskich pacjentów z cukrzycą typu 2 leczonych podstawową dawką insuliny — wyniki badania ORBIT (Observational Registry of Basal Insulin Treatment)

Introduction: This study evaluates an insulin dose titration model and factors that impact insulin dose adjustment in Chinese adults with type-2 diabetes, who receive basal insulin in real-world settings. Material and methods: A total of 19,894 patients from the ORBIT study were included. These patients were divided into four groups, according to the type of insulin dose adjustment: no insulin titration (group A), self-titration (group B), physician-led insulin titration (group C), and combined physician and patient-led insulin titration (group D). Data were collected and compared at baseline and after six months of treatment. Results: A total of 12,865 patients completed the visits and were included in the analysis. Among these patients, 3187 (24.8%), 1971 (15.3%), 5165 (40.1%), and 2542 (19.8%) patients were included in groups A, B, C, and D, respectively. The multivariate logistic regression analysis revealed that the duration of diabetes, body mass index, microvascular complications, inpatient days, HbA1C level, and self-monitoring of blood glucose (SMBG) were positively correlated with insulin titration in group B, C, and D, compared with group A. The number of inpatient days and outpatient visits were positively correlated with dose adjustment for physician-led titration, while this was negatively correlated for self-titration. Self-titration encouraged by physicians and home blood glucose monitoring were positively correlated with self-titration and the combined physician and patient-led titration. Conclusions: High HbA1C level, SMBG, long disease duration, microvascular complications, and the encouragement of physicians while initiating insulin use prompt patients to perform dose adjustments in real-world settings.Wstęp: Badanie ma na celu ocenę modelu dostosowywania dawki insuliny i czynników, mających wpływ na dostosowanie dawki insuliny u chińskich dorosłych pacjentów z cukrzycą typu 2 leczonych podstawową dawką insuliny w warunkach rzeczywistych. Materiał i metody: W badaniu udział wzięło 19 894 pacjentów z badania ORBIT, którzy zostali podzieleni na 4 grupy, w zależności od typu dostosowywania dawki insuliny: brak dostosowywania dawki insuliny (grupa A), samodzielne dostosowywanie dawki (grupa B), dostosowywanie dawki przez lekarza (grupa C) oraz dostosowywanie dawki zarówno przez lekarza jak i przez pacjenta (grupa D). Dane zostały zebrane i porównane na początku badania i po 6 miesiącach leczenia. Wyniki: Łącznie 12 865 pacjentów ukończyło wizyty i zostało uwzględnionych w analizie. Spośród tych pacjentów, 3187 (24,8%), 1971 (15,3%), 5165 (40,1%) i 2542 (19,8%) badanych włączono odpowiednio do grup A, B, C i D. Wieloczynnikowa analiza regresji logistycznej wykazała, że czas trwania cukrzycy, wskaźnik masy ciała, powikłania mikronaczyniowe, dni hospitalizacji, stężenie HbA1C i samokontrola stężenia glukozy we krwi (self-monitoring of blood glucose; SMBG) były dodatnio skorelowane z dostosowywaniem insuliny w grupach B, C i D w porównaniu z grupą A. Liczba dni hospitalizacji i wizyt ambulatoryjnych były dodatnio skorelowane z dostosowywaniem dawek przez lekarza i ujemnie skorelowane z samodzielnym dostosowywaniem dawki. Zachęcanie przez lekarzy do samodzielnego do­stosowywania dawki i monitorowanie stężenia glukozy we krwi w warunkach domowych były dodatnio skorelowane z samodzielnym dostosowywaniem dawki oraz dostosowywaniem dawki zarówno przez lekarza, jak i przez pacjenta. Wnioski: Wysokie stężenie HbA1C, samokontrola stężenia glukozy we krwi, długi czas trwania choroby, powikłania mikronaczyniowe oraz zachęta lekarzy podczas inicjowania podawania insuliny skłaniają pacjentów do dostosowywania dawek w warunkach rzeczywistych

Post-treatment with the GLP-1 analogue liraglutide alleviate chronic inflammation and mitochondrial stress induced by Status epilepticus

Glucagon-like peptide-1(GLP-1) is a growth factor that has neuroprotective and anti-inflammatory properties. The protease resistant GLP-1 analogue liraglutide has been shown to be neuroprotective in previous studies in animal models of Alzheimer’s disease or Parkinson’s disease. Status epilepticus (SE) is a complex disorder, involving many underlying pathological processes, including excitotoxic and chronic inflammatory events. The present pilot study aims to investigate whether liraglutide alleviates the chronic inflammation response and mitochondrial stress induced by SE in the lithium-pilocarpine animal model. We found that treatment with 25nmol/kg. i.p. once-daily after the induction of SE for 7 days reduced chronic inflammation as shown by reduced numbers of activated microglia and astrocytes, and reduced levels of TNF-α and IL-1ß in the hippocampus. The mitochondrial stress marker BAX was reduced and the survival factor Bcl-2 was enhanced by liraglutide. Blood glucose levels were not affected by liraglutide. We show for the first time that liraglutide can reduce the chronic inflammation and mitochondrial stress induced by SE, and the results suggest that GLP-1 receptor agonists such as liraglutide have restorative and protective effects in the brain after SE and could serve as a potential treatment