Generation of genuine entanglement up to 51 superconducting qubits.

Scalable generation of genuine multipartite entanglement with an increasing number of qubits is important for both fundamental interest and practical use in quantum-information technologies1,2. On the one hand, multipartite entanglement shows a strong contradiction between the prediction of quantum mechanics and local realization and can be used for the study of quantum-to-classical transition3,4. On the other hand, realizing large-scale entanglement is a benchmark for the quality and controllability of the quantum system and is essential for realizing universal quantum computing5-8. However, scalable generation of genuine multipartite entanglement on a state-of-the-art quantum device can be challenging, requiring accurate quantum gates and efficient verification protocols. Here we show a scalable approach for preparing and verifying intermediate-scale genuine entanglement on a 66-qubit superconducting quantum processor. We used high-fidelity parallel quantum gates and optimized the fidelitites of parallel single- and two-qubit gates to be 99.91% and 99.05%, respectively. With efficient randomized fidelity estimation9, we realized 51-qubit one-dimensional and 30-qubit two-dimensional cluster states and achieved fidelities of 0.637 ± 0.030 and 0.671 ± 0.006, respectively. On the basis of high-fidelity cluster states, we further show a proof-of-principle realization of measurement-based variational quantum eigensolver10 for perturbed planar codes. Our work provides a feasible approach for preparing and verifying entanglement with a few hundred qubits, enabling medium-scale quantum computing with superconducting quantum systems.

NFIC mediates m6A mRNA methylation to orchestrate transcriptional and post-transcriptional regulation to represses malignant phenotype of non-small cell lung cancer cells.

BACKGROUND: Multiple genetic and epigenetic regulatory mechanisms are crucial in the development and tumorigenesis process. Transcriptional regulation often involves intricate relationships and networks with post-transcriptional regulatory molecules, impacting the spatial and temporal expression of genes. However, the synergistic relationship between transcription factors and N6-methyladenosine (m6A) modification in regulating gene expression, as well as their influence on the mechanisms underlying the occurrence and progression of non-small cell lung cancer (NSCLC), requires further investigation. The present study aimed to investigate the synergistic relationship between transcription factors and m6A modification on NSCLC. METHODS: The transcription factor NFIC and its potential genes was screened by analyzing publicly available datasets (ATAC-seq, DNase-seq, and RNA-seq). The association of NFIC and its potential target genes were validated through ChIP-qPCR and dual-luciferase reporter assays. Additionally, the roles of NFIC and its potential genes in NSCLC were detected in vitro and in vivo through silencing and overexpression assays. RESULTS: Based on multi-omics data, the transcription factor NFIC was identified as a potential tumor suppressor of NSCLC. NFIC was significantly downregulated in both NSCLC tissues and cells, and when NFIC was overexpressed, the malignant phenotype and total m6A content of NSCLC cells was suppressed, while the PI3K/AKT pathway was inactivated. Additionally, we discovered that NFIC inhibits the expression of METTL3 by directly binding to its promoter region, and METTL3 regulates the expression of KAT2A, a histone acetyltransferase, by methylating the m6A site in the 3'UTR of KAT2A mRNA in NSCLC cells. Intriguingly, NFIC was also found to negatively regulate the expression of KAT2A by directly binding to its promoter region. CONCLUSIONS: Our findings demonstrated that NFIC suppresses the malignant phenotype of NSCLC cells by regulating gene expression at both the transcriptional and post-transcriptional levels. A deeper comprehension of the genetic and epigenetic regulatory mechanisms in tumorigenesis would be beneficial for the development of personalized treatment strategies.

Porphyrin-Based Conjugated Microporous Polymer Loaded with Nanoscale Zerovalent Iron for the Degradation of Organic Pollutants under Visible Light.

The degradation of organic dye from waterbodies is of great significance for clean production and environmental remediation. Herein, two porphyrin-based conjugated microporous polymers (CMPs) loaded with nanoscale zerovalent iron (named as Por-CMPs-1-2@nZVI) were successfully fabricated by Sonogashira-Hagihara coupling reactions and the liquid-phase method. The as-synthesized Por-CMPs-1-2@nZVI composites were characterized by various means of analysis, and it was confirmed that Por-CMPs-1-2 loaded with nZVI had good photocatalytic performance. Calculated by ultraviolet-visible spectrum, the band-gap energies of Por-CMPs-1@nZVI and Por-CMPs-2@nZVI were 1.45 and 1.32 eV, respectively, indicating that both can be activated by visible light. The photodegradation of organic dye experiments demonstrated that Por-CMPs-2@nZVI degraded 98.0% of 10 ppm Methylene Blue (MB) within 150 min, which is higher than that of Por-CMPs-1-2 and Por-CMPs-1@nZVI. The experiment of active substance capture and mechanism of ESR confirmed that superoxide anion and hydroxyl radical were the primary valid substances in the photodegradation process of MB. In addition, the preparation of membrane materials was shown to be a successful strategy to realize engineered scale-up production.

One-pot synthesis of NiCo-phyllosilicate supported on zeolite for enhanced degradation of antibiotic contaminants.

The overuse of antibiotics currently results in the presence of various antibiotics being detected in water bodies, which poses potential risks to human health and the environment. Therefore, it is highly significant to remove antibiotics from water. In this study, we developed novel rod-like NiCo-phyllosilicate hybrid catalysts on calcined natural zeolite (NiCo@C-zeolite) via a facile one-pot process. The presence of the zeolite served as both a silicon source and a support, maintaining a high specific surface area of the NiCo@C-zeolite. Remarkably, NiCo@C-zeolite exhibited outstanding catalytic performance in antibiotic degradation under PMS activation. Within just 5 min, the degradation rate of metronidazole (MNZ) reached 96.14%, ultimately achieving a final degradation rate of 99.28%. Furthermore, we investigated the influence of catalyst dosage, PMS dosage, MNZ concentration, initial pH value, and various inorganic anions on the degradation efficiency of MNZ. The results demonstrated that NiCo@C-zeolite displayed outstanding efficacy in degrading MNZ under diverse conditions and maintained a degradation rate of 94.86% at 60 min after three consecutive cycles of degradation. Free radical quenching experiments revealed that SO•-4played a significant role in the presence of NiCo@C-zeolite-PMS system. These findings indicate that the novel rod-like NiCo-phyllosilicate hybrid catalysts had excellent performance in antibiotic degradation.

New Transferrin Receptor-Targeted Peptide-Doxorubicin Conjugates: Synthesis and In Vitro Antitumor Activity.

Poor selectivity to tumor cells is a major drawback in the clinical application of the antitumor drug doxorubicin (DOX). Peptide-drug conjugates (PDCs) constructed by modifying antitumor drugs with peptide ligands that have high affinity to certain overexpressed receptors in tumor cells are increasingly assessed for their possibility of tumor-selective drug delivery. However, peptide ligands composed of natural L-configuration amino acids have the defects of easy enzymatic degradation and insufficient biological stability. In this study, two new PDCs (LT7-SS-DOX and DT7-SS-DOX) were designed and synthesized by conjugating a transferrin receptor (TfR) peptide ligand LT7 (HAIYPRH) and its retro-inverso analog DT7 (hrpyiah), respectively, with DOX via a disulfide bond linker. Both conjugates exhibited targeted antiproliferative effects on TfR overexpressed tumor cells and little toxicity to TfR low-expressed normal cells compared with free DOX. Moreover, the DT7-SS-DOX conjugate possessed higher serum stability, more sustained reduction-triggered drug release characteristics, and stronger in vitro antiproliferative activity as compared to LT7-SS-DOX. In conclusion, the coupling of antitumor drugs with the DT7 peptide ligand can be used as a promising strategy for the further development of stable and efficient PDCs with the potential to facilitate TfR-targeted drug delivery.

PiLSL: pairwise interaction learning-based graph neural network for synthetic lethality prediction in human cancers.

MOTIVATION: Synthetic lethality (SL) is a type of genetic interaction in which the simultaneous inactivation of two genes leads to cell death, while the inactivation of a single gene does not affect the cell viability. It can effectively expand the range of anti-cancer therapeutic targets. SL interactions are identified mainly by experimental screening and computational prediction. Recent machine-learning methods mostly learn the representation of each gene individually, ignoring the representation of the pairwise interaction between two genes. In addition, the mechanisms of SL, the key to translating SL into cancer therapeutics, are often unclear. RESULTS: To fill the gaps, we propose a pairwise interaction learning-based graph neural network (GNN) named PiLSL to learn the representation of pairwise interaction between two genes for SL prediction. First, we construct an enclosing graph for each pair of genes from a knowledge graph. Secondly, we design an attentive embedding propagation layer in a GNN to discriminate the importance among the edges in the enclosing graph and to learn the latent features of the pairwise interaction from the weighted enclosing graph. Finally, we further fuse the latent features with explicit features extracted from multi-omics data to obtain powerful gene representations for SL prediction. Extensive experimental results demonstrate that PiLSL outperforms the best baseline by a large margin and generalizes well under three realistic scenarios. Besides, PiLSL provides an explanation of SL mechanisms via the weighted paths in the enclosing graphs by attention mechanism. AVAILABILITY AND IMPLEMENTATION: Our source code is available at https://github.com/JieZheng-ShanghaiTech/PiLSL.

Logical Magic State Preparation with Fidelity beyond the Distillation Threshold on a Superconducting Quantum Processor.

Fault-tolerant quantum computing based on surface code has emerged as an attractive candidate for practical large-scale quantum computers to achieve robust noise resistance. To achieve universality, magic states preparation is a commonly approach for introducing non-Clifford gates. Here, we present a hardware-efficient and scalable protocol for arbitrary logical state preparation for the rotated surface code, and further experimentally implement it on the Zuchongzhi 2.1 superconducting quantum processor. An average of 0.8983±0.0002 logical fidelity at different logical states with distance three is achieved, taking into account both state preparation and measurement errors. In particular, the logical magic states |A^{π/4}⟩_{L}, |H⟩_{L}, and |T⟩_{L} are prepared nondestructively with logical fidelities of 0.8771±0.0009, 0.9090±0.0009, and 0.8890±0.0010, respectively, which are higher than the state distillation protocol threshold, 0.859 (for H-type magic state) and 0.827 (for T-type magic state). Our work provides a viable and efficient avenue for generating high-fidelity raw logical magic states, which is essential for realizing non-Clifford logical gates in the surface code.

A meta-analysis of the risk factors for surgical site infection in patients with colorectal cancer.

The purpose of the meta-analysis was to evaluate and compare the surgical site infection (SSI) risk factors in patients with colorectal cancer (CC). The results of this meta-analysis were analysed, and the odds ratio (OR) and mean difference (MD) with 95% confidence intervals (CIs) were calculated using dichotomous or contentious random or fixed-effect models. For the current meta-analysis, 23 examinations spanning from 2001 to 2023 were included, encompassing 89 859 cases of CC. Clean-contaminated surgical site wounds had significantly lower infections (OR, 0.36; 95% CI, 0.20-0.64, p < 0.001) compared to contaminated surgical site wounds in patients with CCs. Males had significantly higher SSIs (OR, 1.18; 95% CI, 1.12-1.24, p < 0.001) compared to females in patients with CC. American Society of Anesthesiology score ≥3 h had a significantly higher SSI (OR, 1.42; 95% CI, 1.18-1.71, p < 0.001) compared to <3 score in patients with CCs. Body mass index ≥25 had significantly higher SSIs (OR, 1.54; 95% CI, 1.11-2.14, p = 0.01) compared to <25 in patients with CCs. The presence of stoma creation had a significantly higher SSI rate (OR, 2.28; 95% CI, 1.37-3.79, p = 0.001) compared to its absence in patients with CC. Laparoscopic surgery had significantly lower SSIs (OR, 0.68; 95% CI, 0.59-0.78, p < 0.001) compared to open surgery in patients with CC. The presence of diabetes mellitus had a significantly higher SSI rate (OR, 1.24; 95% CI, 1.15-1.33, p < 0.001) compared to its absence in patients with CCs. No significant difference was found in SSI rate in patients with CCs between <3 and ≥3 h of operative time (OR, 1.07; 95% CI, 0.75-1.51, p = 0.72), between the presence and absence of blood transfusion (OR, 1.60; 95% CI, 0.69-3.66, p = 0.27) and between the presence and absence of previous laparotomies (OR, 1.47; 95% CI, 0.93-2.32, p = 0.10). The examined data revealed that contaminated wounds, male sex, an American Society of Anesthesiology score ≥3 h, a body mass index ≥25, stoma creation, open surgery and diabetes mellitus are all risk factors for SSIs in patients with CC. However, operative time, blood transfusion and previous laparotomies were not found to be risk factors for SSIs in patients with CC. However, given that several comparisons had a small number of chosen research, consideration should be given to their values.

A Novel Dendrite-Free Lithium Metal Anode via Oxygen and Boron Codoped Honeycomb Carbon Skeleton.

Lithium (Li) metal is an excellent anode of Li ion batteries because of its high theoretical capacity and the low redox potential compared to other anodes. However, the uncontrollable growth of Li dendrites still incurs serious safety issues and poor electrochemical performances, leading to its limited practical application. An oxygen and boron codoped honeycomb carbon skeleton (OBHcCs) is reported and a stable Li metal-based anode is realized. It can be coated on a copper foil substrate to be used as a current collector for a dendrite-free Li metal anode. OBHcCs effectively reduces the local current density owing to the high surface area and inhibits Li dendrite growth, which is explored by scanning electron microscopy and an X-ray photoelectron spectra depth profile. The abundant lithiophilic oxygen and boron-containing functional groups reduce the potential barrier of nucleation and lead to the homogeneous Li ions flux as confirmed by the density functional theories. Therefore, the Li metal anode based on OBHcCs (OBHcCs@Li) stably runs for 700 h in a symmetric cell with a Li stripping capacity of 1 mAh cm-2 at 1 mA cm-2 . Furthermore, the OBHcCs@Li|LiFePO4 full cell shows a good capacity retention of 84.6% with a high coulombic efficiency of 99.6% at 0.5 C for 500 cycles.

Observation of Thermalization and Information Scrambling in a Superconducting Quantum Processor.

Understanding various phenomena in nonequilibrium dynamics of closed quantum many-body systems, such as quantum thermalization, information scrambling, and nonergodic dynamics, is crucial for modern physics. Using a ladder-type superconducting quantum processor, we perform analog quantum simulations of both the XX-ladder model and the one-dimensional XX model. By measuring the dynamics of local observables, entanglement entropy, and tripartite mutual information, we signal quantum thermalization and information scrambling in the XX ladder. In contrast, we show that the XX chain, as free fermions on a one-dimensional lattice, fails to thermalize to the Gibbs ensemble, and local information does not scramble in the integrable channel. Our experiments reveal ergodicity and scrambling in the controllable qubit ladder, and open the door to further investigations on the thermodynamics and chaos in quantum many-body systems.

Realization of an Error-Correcting Surface Code with Superconducting Qubits.

Quantum error correction is a critical technique for transitioning from noisy intermediate-scale quantum devices to fully fledged quantum computers. The surface code, which has a high threshold error rate, is the leading quantum error correction code for two-dimensional grid architecture. So far, the repeated error correction capability of the surface code has not been realized experimentally. Here, we experimentally implement an error-correcting surface code, the distance-three surface code which consists of 17 qubits, on the Zuchongzhi 2.1 superconducting quantum processor. By executing several consecutive error correction cycles, the logical error can be significantly reduced after applying corrections, achieving the repeated error correction of surface code for the first time. This experiment represents a fully functional instance of an error-correcting surface code, providing a key step on the path towards scalable fault-tolerant quantum computing.

Tracking of menstrual cycles and prediction of the fertile window via measurements of basal body temperature and heart rate as well as machine-learning algorithms.

BACKGROUND: Fertility awareness and menses prediction are important for improving fecundability and health management. Previous studies have used physiological parameters, such as basal body temperature (BBT) and heart rate (HR), to predict the fertile window and menses. However, their accuracy is far from satisfactory. Additionally, few researchers have examined irregular menstruators. Thus, we aimed to develop fertile window and menstruation prediction algorithms for both regular and irregular menstruators. METHODS: This was a prospective observational cohort study conducted at the International Peace Maternity and Child Health Hospital in Shanghai, China. Participants were recruited from August 2020 to November 2020 and followed up for at least four menstrual cycles. Participants used an ear thermometer to assess BBT and wore the Huawei Band 5 to record HR. Ovarian ultrasound and serum hormone levels were used to determine the ovulation day. Menstruation was self-reported by women. We used linear mixed models to assess changes in physiological parameters and developed probability function estimation models to predict the fertile window and menses with machine learning. RESULTS: We included data from 305 and 77 qualified cycles with confirmed ovulations from 89 regular menstruators and 25 irregular menstruators, respectively. For regular menstruators, BBT and HR were significantly higher during fertile phase than follicular phase and peaked in the luteal phase (all P < 0.001). The physiological parameters of irregular menstruators followed a similar trend. Based on BBT and HR, we developed algorithms that predicted the fertile window with an accuracy of 87.46%, sensitivity of 69.30%, specificity of 92.00%, and AUC of 0.8993 and menses with an accuracy of 89.60%, sensitivity of 70.70%, and specificity of 94.30%, and AUC of 0.7849 among regular menstruators. For irregular menstruators, the accuracy, sensitivity, specificity and AUC were 72.51%, 21.00%, 82.90%, and 0.5808 respectively, for fertile window prediction and 75.90%, 36.30%, 84.40%, and 0.6759 for menses prediction. CONCLUSIONS: By combining BBT and HR recorded by the Huawei Band 5, our algorithms achieved relatively ideal performance for predicting the fertile window and menses among regular menstruators. For irregular menstruators, the algorithms showed potential feasibility but still need further investigation. TRIAL REGISTRATION: ChiCTR2000036556. Registered 24 August 2020.

Porphyrin-Based Conjugated Microporous Polymers for Highly Efficient Adsorption of Metal Ions.

The capture and elimination of anions and cations from water have attracted a great deal of attention and are quite vital for clean production and environmental remediation. In this work, we present the synthesis of four porphyrin (Por)-based conjugated microporous polymers (CMPs, namely, Por-CMP-1-4), which were produced through a Sonogashira-Hagihara linked response using porphyrin and acetylene aromatic compounds as building blocks and used as absorbents to eliminate metal ions from water. The as-synthesized Por-CMP-1-4 exhibit an amorphous porous structure and outstanding caloric and physicochemical properties. Taking advantage of their larger specific surface areas, i.e., 541.47, 614.58, 382.38, and 677.90 m2 g-1 for Por-CMP-1-4, respectively, and their chelating active site that originated from the porphyrin ring, Por-CMP-1-4 show better Zn2+, Cu2+, and Pb2+ adsorption ability. Among them, Por-CMP-3 has the greatest adsorbability of 640 mg g-1 for Zn2+, with an adsorption efficiency of 80%, whereas its adsorption capacities for Cu2+ and Pb2+ ions were both 334 mg g-1, with an adsorption efficiency of 42% for Cu2+ and Pb2+. Employing Por-CMP-3 as a representative example, its adsorption kinetics has been systematically investigated. The adsorption behavior of Por-CMP-3 with respect to the Zn2+ ion is shown to exhibit pseudo-first-order kinetics and Langmuir isotherm modes. Meanwhile, the adsorption mechanism is discussed in detail, and it was thought it might be chelation, in which the nitrogen atoms with a single pair of electrons on the porphyrin ring interacted with metal ions to form stable chelation coordination bonds, thus removing metal ions selectively and effectively. Furthermore, Por-CMP-3 exhibited good reusability, retaining 60% of its Zn2+ removal rate after four continuous adsorptions.

Interactive effects of ambient air pollution and sunshine duration on the risk of intrahepatic cholestasis of pregnancy.

INTRODUCTION: While the associations among ambient pollutants and various pregnancy complications are well documented, the effect of ambient pollutants on intrahepatic cholestasis of pregnancy (ICP) has not been examined. This study aimed to explore the effects of ambient pollutants and sunshine duration on ICP. METHODS: The study enrolled 169,971 pregnant women who delivered between 2015 and 2020 in two hospitals. The associations between ICP and exposure to ambient pollutants and sunshine duration, averaged throughout different periods (including the 3 months before conception, 1st trimester and 2nd trimester), were estimated using a generalized linear model. The interaction effects of ambient pollutants and sunshine duration on ICP were estimated. RESULTS: The fitted curves for ICP incidence were similar to the temporal trends of PM2.5, PM10, SO2, CO and NO2 but not that of O3. The risk of ICP was significantly elevated following a 10-µg/m3 increase in PM2.5 (aOR [adjusted odds ratio] = 1.057, 95% CI [confidence interval]: 1.017-1.099) and PM10 (aOR = 1.043, 95% CI: 1.013-1.074) and a 1-h decrease in sunshine duration (aOR = 1.039, 95% CI: 1.011-1.068) during the 3 months before conception. In the second trimester, a 1-µg/m3 increase in the concentration of SO2 was associated with an increased risk of ICP (aOR = 1.011, 95% CI: 1.001-1.021). Increased concentrations of PM2.5 and PM10 had interactive effects with reduced sunshine duration during the 3 months before conception on increasing the risk of ICP. CONCLUSIONS: Exposure to PM2.5 and PM10 during the 3 months before conception and exposure to SO2 in the second trimester were associated with an increased ICP risk. Reduced sunshine duration had an interactive effect with increased concentrations of PM2.5 and PM10 during the 3 months before conception on the occurrence of ICP.

Association between prenatal exposure to ambient air pollutants and postpartum depressive symptoms: A multi-city cohort study.

BACKGROUND: Women are vulnerable to depression during postpartum period. While several studies have shown associations between ambient air pollution exposure and depression in general population, there was few studies focused on the effect of various air pollutants on postpartum depression (PPD). OBJECTIVE: This study is designed to explore the association between prenatal exposure to air pollutants and PPD, and to reveal the potential vulnerable exposure time point. METHODS: The study enrolled 10,209 pregnant women who delivered between October 2019 and February 2021 in 5 participating hospitals from 3 cities in China. Edinburgh Postnatal Depression Scale (EPDS) was administered at 6 weeks postpartum to identify PPD symptoms. Associations between PPD symptoms and exposure levels in PM2.5, PM10, SO2, CO, NO2, and O3 averaged over the whole pregnancy and each trimester were estimated using logistic regression models after adjusting for potential confounding factors. Distributed lag models (DLMs) were used to determine the relevant associations in each gestational week. RESULTS: The risk for developing PPD symptoms was significant following a 10 µg/m3 increase in PM10 (aOR = 1.47, 95%CI:1.36-1.59), NO2 (aOR = 1.63, 95%CI:1.44-1.85), and 0.1 mg/m3 increase in CO (aOR = 2.31, 95%CI: 1.99-2.69) during the whole pregnancy. Similar results were also found in exposure during each trimester of pregnancy. Besides, SO2 exposure during the second trimester was a major risk factor for developing PPD symptoms (aOR = 1.10, 95%CI:1.03-1.18). Consistent effects were also observed in DLMs, except for PM2.5 and O3, which showed no significant sensitive windows throughout pregnancy period. CONCLUSION: Exposure to PM10, CO, NO2, and SO2 in pregnancy is associated with increased risks of developing depression at 6 weeks postpartum. Our findings reveal the importance of air pollution control for preventing maternal mental health disorders among the public.

Antepartum sleep quality, mental status, and postpartum depressive symptoms: a mediation analysis.

BACKGROUND: Poor sleep quality and maternal mood disturbances are common during pregnancy and may play pivotal roles in the development of postpartum depression. We aim to examine the trajectories of sleep quality and mental health in women from early pregnancy to delivery and explore the mediating effects of sleep quality and mental status on the link between antepartum depressive symptoms and postpartum depressive symptoms. METHODS: In an ongoing prospective birth cohort, 1301 women completed questionnaires in the first, second and third trimesters and at 6 weeks postpartum. In each trimester, sleep quality was measured utilizing the Pittsburgh Sleep Quality Index (PSQI), and mental health was assessed with the Center for Epidemiologic Studies Depression Scale (CES-D), the Self-Rating Anxiety Scale (SAS) and the Perceived Stress Scale (PSS). Postpartum depressive symptoms were evaluated by the Edinburgh Postnatal Depression Scale (EPDS). The bootstrap method was used to test the mediation effect. RESULTS: The PSQI, CES-D, and SAS scores presented U-shaped curves across the antenatal period while the PSS score followed a descending trend. Antenatal sleep quality, depressive symptoms, anxiety symptoms and perceived stress all predicted depressive symptoms at 6 weeks postpartum. The influence of antepartum depressive symptoms on postpartum depressive symptoms was mediated by antepartum sleep quality and anxiety symptoms, which accounted for 32.14%, 39.25% and 31.25% in the first, second and third trimesters (P = 0.002, P = 0.001, P = 0.001, respectively). CONCLUSIONS: Poor sleep quality and anxiety symptoms in pregnancy mediated the relationship between antepartum depressive symptoms and postpartum depressive symptoms. Interventions aimed at detecting and managing sleep quality and elevated anxiety among depressed women in pregnancy warrant further investigation as preventative strategies for postpartum depression.

Per1/Per2 knockout Affects Spleen Immune Function in Elderly Mice via Inducing Spleen Lymphocyte Ferroptosis.

Disturbances in circadian rhythms are known to affect immune functions. However, the long-term impact of abnormal circadian rhythms on the immune-related functions of the spleen are poorly understood. Hence, we aimed to investigate the immune-related functions of spleen in Per1/Per2 double-knockout (DKO) and wild-type (WT) mice aged 4, 9, and 14 months. Compared to the WT mice, the DKO mice had smaller spleen white pulp (WP) and lymphocyte germinal area, as well as fewer immune cells with age-these differences were especially clear. The spleen lymphocyte mortality, malondialdehyde (MDA) levels, reactive oxygen species (ROS) levels, and ferritin-binding receptor (TFR1) levels were significantly higher in the 14-month-old DKO mice than in WT mice of the same age. Transcriptome analysis showed that most of the differentially expressed mRNAs were enriched in DNA damage repair-related pathways. In DKO mice, spleen cells showed up-regulation of pro-ferroptosis genes, such as Cd36,Atm, and Acsl4, and down-regulation of anti-ferroptosis genes, such as GPX4. We found that long-term abnormalities in the circadian rhythm can induce DNA damage and ferroptosis in mouse spleen.

Anxiety and depression-like behaviours are more frequent in aged male mice conceived by ART compared with natural conception.

The number of children born after assisted reproductive technology (ART) is accumulating rapidly, and the health problems of the children are extensively concerned. This study aims to evaluate whether ART procedures alter behaviours in male offspring. Mouse models were utilized to establish three groups of offspring conceived by natural conception (NC), in vitro fertilization and embryo transfer (IVF-ET), and frozen-thawed embryo transfer (IVF-FET), respectively. A battery of behaviour experiments for evaluating anxiety and depression levels, including the open field test (OFT), elevated plus maze (EPM) test, light/dark transition test (L/DTT), tail suspension test (TST), forced swimming test (FST), and sucrose preference test (SPT) was carried out. Aged (18 months old), but not young (3 months old), male offspring in the IVF-ET and IVF-FET groups, compared with those in the NC group, exhibited increased anxiety and depression-like behaviours. The protein expression levels of three neurotrophins in PFC or hippocampus in aged male offspring from the IVF-ET and IVF-FET groups reduced at different extent, in comparison to NC group. RNA sequencing (RNA-Seq) was performed in the hippocampus of 18 months old offspring to further explore the gene expression profile changes in the three groups. KEGG analyses revealed the coexisted pathways, such as PI3K-Akt signalling pathway, which potentially reflected the similarity and divergence in anxiety and depression between the offspring conceived by IVF-ET and IVF-FET. Our research suggested the adverse effects of advanced age on the psychological health of children born after ART should be highlighted in the future.

Observation of Strong and Weak Thermalization in a Superconducting Quantum Processor.

We experimentally study the ergodic dynamics of a 1D array of 12 superconducting qubits with a transverse field, and identify the regimes of strong and weak thermalization with different initial states. We observe convergence of the local observable to its thermal expectation value in the strong-thermalizaion regime. For weak thermalization, the dynamics of local observable exhibits an oscillation around the thermal value, which can only be attained by the time average. We also demonstrate that the entanglement entropy and concurrence can characterize the regimes of strong and weak thermalization. Our work provides an essential step toward a generic understanding of thermalization in quantum systems.

Strong Quantum Computational Advantage Using a Superconducting Quantum Processor.

Scaling up to a large number of qubits with high-precision control is essential in the demonstrations of quantum computational advantage to exponentially outpace the classical hardware and algorithmic improvements. Here, we develop a two-dimensional programmable superconducting quantum processor, Zuchongzhi, which is composed of 66 functional qubits in a tunable coupling architecture. To characterize the performance of the whole system, we perform random quantum circuits sampling for benchmarking, up to a system size of 56 qubits and 20 cycles. The computational cost of the classical simulation of this task is estimated to be 2-3 orders of magnitude higher than the previous work on 53-qubit Sycamore processor [Nature 574, 505 (2019)NATUAS0028-083610.1038/s41586-019-1666-5. We estimate that the sampling task finished by Zuchongzhi in about 1.2 h will take the most powerful supercomputer at least 8 yr. Our work establishes an unambiguous quantum computational advantage that is infeasible for classical computation in a reasonable amount of time. The high-precision and programmable quantum computing platform opens a new door to explore novel many-body phenomena and implement complex quantum algorithms.