Quafu-Qcover:Explore combinatorial optimization problems on cloud-based quantum computers

We introduce Quafu-Qcover,an open-source cloud-based software package developed for solving combinatorial optimization problems using quantum simulators and hardware backends.Quafu-Qcover provides a standardized and comprehensive workflow that utilizes the quantum approximate optimization algorithm(QAOA).It facilitates the automatic conversion of the original problem into a quadratic unconstrained binary optimization(QUBO)model and its corresponding Ising model,which can be subsequently transformed into a weight graph.The core of Qcover relies on a graph decomposition-based classical algorithm,which efficiently derives the optimal parameters for the shallow QAOA circuit.Quafu-Qcover incorporates a dedicated compiler capable of translating QAOA circuits into physical quantum circuits that can be executed on Quafu cloud quantum computers.Compared to a general-purpose compiler,our compiler demonstrates the ability to generate shorter circuit depths,while also exhibiting superior speed performance.Additionally,the Qcover compiler has the capability to dynamically create a library of qubits coupling substructures in real-time,utilizing the most recent calibration data from the superconducting quantum devices.This ensures that computational tasks can be assigned to connected physical qubits with the highest fidelity.The Quafu-Qcover allows us to retrieve quantum computing sampling results using a task ID at any time,enabling asynchronous processing.Moreover,it incorporates modules for results preprocessing and visualization,facilitating an intuitive display of solutions for combinatorial optimization problems.We hope that Quafu-Qcover can serve as an instructive illustration for how to explore application problems on the Quafu cloud quantum computers.

Quafu-RL:The cloud quantum computers based quantum reinforcement learning

With the rapid advancement of quantum computing,hybrid quantum–classical machine learning has shown numerous potential applications at the current stage,with expectations of being achievable in the noisy intermediate-scale quantum(NISQ)era.Quantum reinforcement learning,as an indispensable study,has recently demonstrated its ability to solve standard benchmark environments with formally provable theoretical advantages over classical counterparts.However,despite the progress of quantum processors and the emergence of quantum computing clouds,implementing quantum reinforcement learning algorithms utilizing parameterized quantum circuits(PQCs)on NISQ devices remains infrequent.In this work,we take the first step towards executing benchmark quantum reinforcement problems on real devices equipped with at most 136 qubits on the BAQIS Quafu quantum computing cloud.The experimental results demonstrate that the policy agents can successfully accomplish objectives under modified conditions in both the training and inference phases.Moreover,we design hardware-efficient PQC architectures in the quantum model using a multi-objective evolutionary algorithm and develop a learning algorithm that is adaptable to quantum devices.We hope that the Quafu-RL can be a guiding example to show how to realize machine learning tasks by taking advantage of quantum computers on the quantum cloud platform.

扰动系数预测不同年龄重型颅脑损伤患儿预后的临床价值

目的探讨无创脑水肿动态监护仪扰动系数对不同年龄重型颅脑损伤患儿预后判定的临床价值。方法选取2018年10月—2021年5月南京医科大学附属无锡儿童医院收治的颅脑损伤患儿131例作为研究对象。根据患儿年龄分为1~3岁组、>3~5岁组、>5~14岁组,分别有40例、44例和47例。根据颅脑损伤手术后6个月的预后,采用Logistic回归分析不同年龄患儿颅脑损伤预后的影响因素,采用受试者工作特征(ROC)曲线分析无创脑水肿动态监护仪扰动系数预测不同年龄患儿颅脑损伤预后的价值。结果各组体重、GCS评分、颅内压、CK-MB、前白蛋白、白蛋白、扰动系数比较,差异有统计学意义(P<0.05)。共60例(46.51%)患儿预后不良。各组总预后不良率比较,差异无统计学意义(P>0.05)。多因素Logistic回归分析结果:乳酸[OR=4.092(95%CI:1.684,9.945)、3.846(95%CI:1.582,9.347)、4.067(95%CI:1.674,9.885)]、GCS评分[OR=3.364(95%CI:1.384,8.175)、3.313(95%CI:1.363,8.053)、4.200(95%CI:1.728,10.207)]、扰动系数[OR=3.699(95%CI:1.522,8.989)、3.892(95%CI:1.602,9.460)、4.125(95%CI:1.697,10.024)]是影响1~3岁、>3~5岁、>5~14岁颅脑损伤患儿预后的独立因素(P<0.05)。ROC曲线结果显示:无创脑水肿动态监护仪扰动系数预测1~3岁组、>3~5岁组、>5~14岁组患儿敏感性分别为72.73%(95%CI:0.114,0.560)、73.68%(95%CI:0.102,0.455)、73.68%(95%CI:0.119,0.466),特异性分别为70.59%(95%CI:0.116,0.504)、76.00%(95%CI:0.101,0.514)、74.07%(95%CI:0.101,0.514)。结论不同年龄重型颅脑损伤患儿预后不良风险高,无创脑水肿动态监护仪扰动系数预测1~3岁、>3~5岁、>5~14岁颅脑损伤患儿预后的效能良好。

Diabetes onset at an earlier age and high HbA1c levels as risk factors of diabetic retinopathy

AIM:To assess the effect of age at diabetes onset and uncontrollable high Hb A1 c levels on the development of diabetic retinopathy(DR)among Chinese type 2 diabetes mellitus(DM)patients.METHODS:This was a cross-sectional survey of diabetic patients in Subei district,China.Data covering physical measurements,fasting blood-glucose(FBG),glycosylated hemoglobin(Hb A1 c),blood lipid,urinary albumin/creatinine ratio(UACR),ocular fundus examination,and diabetes treatment records were collected.An independent sample t-test were used to analyze differences.A Logistic regression analysis was applied to study the independent risk factors of DR.RESULTS:A total of 1282 patients with type 2 DM were enrolled,and 191 cases had DR(14.9%).The age at diabetes onset,education level,alcohol consumption,Hb A1 c level,UACR level,and hypoglycemic drugs were independent influencing factors for DR.The older the onset of diabetes,the less likely to develop DR(OR:0.958,95%CI:0.942-0.975,P=0.000).Patients were then divided in terms of age at diabetes onset as follows:<50 y,50-59 y,60-69 y,and≥70 y.Compared with diabetes onset age<50 y,50-59 y(OR:0.463,95%CI:0.306-0.699,P=0.000),60-69 y(OR:0.329,95%CI:0.203-0.535,P=0.000)and≥70 y(OR:0.232,95%CI:0.094-0.577,P=0.002)were at a lower risk of DR.The prevalence of DR was highest in patients with diabetes onset age<50 y(29.5%,P<0.05).The Hb A1 c level(8.67±1.97)%and proportion of insulin injection(52.5%)in patients with diabetes onset<40 y were higher than in patients with older diabetes onset age(P<0.05).CONCLUSION:Diabetes onset at an earlier age and uncontrollable high Hb A1 c level could be independent risk factors for DR.

PPARβ expression in rectus abdominis and abdominal subcutaneous fat of patients with gestational diabetes mellitus and its relationship with glucolipid metabolism

Objective:To study the relationship between peroxisome proliferator-activated receptorβ(PPARβ) expression in rectus abdominis as well as abdominal subcutaneous fat of patients with gestational diabetes mellitus (GDM) and glucolipid metabolism.Methods:The pregnant women who received routine antenatal care and planned to receive selective caesarean section in Obstetrics Department of our hospital between May 2012 and March 2016 were retrospectively analyzed, and 74 healthy pregnant women and 58 pregnant women with GDM were screened and included in the control group and gestational diabetes mellitus group (GDM group) respectively. Rectus abdominis and abdominal subcutaneous fat were collected during Cesarean section to determine the expression of PPARβ was measured;peripheral blood was collected at middle-late pregnancy to determine the content of blood glucose metabolism and lipid metabolism indexes as well as adipocytokines.Results:PARβ mRNA expression and protein expression in rectus abdominis and abdominal subcutaneous fat of GDM group were significantly lower than those of control group (P<0.05);homeostasis model assessment insulin secretion index (HOMA-β), homeostasis model assessment insulin resistance (HOMA-IR) and OGTT glucose curve (AUCG) levels as well as serum low-density lipoprotein cholesterol (LDL-C), triglyceride (TG), cholesterol (TC), Leptin, Resistin and Chemerin content of GDM group were significantly higher than those of control group (P<0.05) while early insulin secretion index (ΔI30/ΔG30) and insulin sensitive index composite (ISIcomp) levels as well as serum high-density lipoprotein cholesterol (HDL-C), Omentin-1 and Omentin-1 and adiponectin (ADPN) content were significantly lower than those of control group (P<0.05);PARβ mRNA expression and protein expression were negatively correlated with HOMA-β, HOMA IR, area under the AUCG, LDL-C, TG, TC, Leptin, Resistin and Chemerin, and positively correlated withΔI30/ΔG30, ISIcomp, HDL-C, and ADPN.Conclusions:PPARβ expression significantly decreases in rectus abdominis and abdominal subcutaneous fat of pregnant womepn with GDM and it is closely related to the abnormal glucolipid metabolism in pregnant women with GDM.

Influence of intraperitoneal perfusion chemotherapy combined with deep hyperthermia on the malignant molecule expression in ascites of patients with ovarian cancer complicated by ascites

Objective: To explore the influence of intraperitoneal perfusion chemotherapy combined with deep hyperthermia on the malignant molecule expression in ascites of patients with ovarian cancer complicated by ascites. Methods: A total of 80 patients with ovarian cancer complicated by ascites who were treated in this hospital between March 2015 and January 2017 were retrospectively analyzed and divided into the control group (n=43) and the study group (n=37). Control group received intraperitoneal perfusion chemotherapy and study group underwent intraperitoneal perfusion chemotherapy combined with deep hyperthermia. The differences in the expression of proliferation, invasion, autophagy and other malignant molecules in ascites were compared between the two groups before and after treatment. Results: Before treatment, the differences in the expression of proliferation, invasion, autophagy and other malignant molecules in ascites were not statistically significant between the two groups. After treatment, proliferation gene TCEAL7 mRNA expression in ascites of study group was higher than that of control group whereas Clusterin, HOTAIR, ROCK and TNFAIP8 mRNA expression were lower than those of control group;invasion gene DUSP10 mRNA expression in ascites was higher than that of control group whereas MTA1, Nek2, Stathmin and IFITM1 mRNA expression were lower than those of control group;autophagy genes LC3-Ⅱ, Beclin1 and PTEN mRNA expression in ascites were higher than those of control group. Conclusion:Intraperitoneal perfusion chemotherapy combined with deep hyperthermia can effectively balance the expression of proliferation, invasion and autophagy genes in ascites, and ultimately reduce the malignancy of the tumor in patients with ovarian cancer complicated by ascites.

Characterization of the metallo-dependent amidohydrolases responsible for“auxiliary”leucinyl removal in the biosynthesis of 2,20-bipyridine antibiotics

2,20-Bipyridine(2,20-BiPy)is an attractive core structure present in a number of biologically active natural products,including the structurally related antibiotics caerulomycins(CAEs)and collismycins(COLs).Their biosynthetic pathways share a similar key 2,20-BiPy-L-leucine intermediate,which is desulfurated or sulfurated at C5,arises from a polyketide synthase/nonribosomal peptide synthetase hybrid assembly line.Focusing on the common off-line modification steps,we here report that the removal of the“auxiliary”L-leucine residue relies on the metallo-dependent amidohydrolase activity of CaeD or ColD.This activity leads to the production of similar 2,20-BiPy carboxylate products that then receive an oxime functionality that is characteristic for both CAEs and COLs.Unlike many metallo-dependent amidohydrolase superfamily proteins that have been previously reported,these proteins(particularly CaeD)exhibited a strong zinc ion-binding capacity that was proven by site-specific mutagenesis studies to be essential to proteolytic activity.The kinetics of the conversions that respectively involve CaeD and ColD were analyzed,showing the differences in the efficiency and substrate specificity of these two proteins.These findings would generate interest in the metallo-dependent amidohydrolase superfamily proteins that are involved in the biosynthesis of bioactive natural products.