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Objective: To introduce a locating device for the entry point of intramedullary nail based on the inertial navigation technology, which utilizes multi-dimensional angle information to assist in rapid and accurate positioning of the ideal direction of femoral anterograde intramedullary nails' entry point, and to verify its clinical value through clinical tests. Methods: After matching the locating module with the developing board, which are the two components of the locating device, they were placed on the skin surface of the proximal femur of the affected side. Anteroposterior fluoroscopy was performed. The developing angle corresponding to the ideal direction of entry point was selected based on the X-ray image, and then the yaw angle of the locating module was reset to zero. After resetting, the locating module was combined with the surgical instrument to guide the insertion angle of the guide wire. The ideal direction of entry point was accurately located based on the angle guidance. By setting up an experimental group and a control group for clinical surgical operations, the number of guide wire insertion times, surgical time, fluoroscopy frequency, and intraoperative blood loss with or without the locating device was recorded. Results: Compared to the control group, the experimental group showed significant improvement in the number of guide wire insertion times, surgical time, fluoroscopy frequency, and intraoperative blood loss, with a statistically significant difference (P<0.01). Conclusion: The locating device can assist doctors in quickly locating the entry point of intramedullary nail, effectively reducing the fluoroscopy frequency and surgical time by improving the success rate of the guide wire insertion with one shot, improving surgical efficiency, and possessing certain clinical value.
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Fijación Intramedular de Fracturas , Cirugía Asistida por Computador , Humanos , Clavos Ortopédicos , Pérdida de Sangre Quirúrgica , Fluoroscopía/métodos , Fijación Intramedular de Fracturas/métodos , Cirugía Asistida por Computador/métodosRESUMEN
Although B cells are implicated in multiple sclerosis (MS) pathophysiology, a predictive or diagnostic autoantibody remains elusive. In this study, the Department of Defense Serum Repository (DoDSR), a cohort of over 10 million individuals, was used to generate whole-proteome autoantibody profiles of hundreds of patients with MS (PwMS) years before and subsequently after MS onset. This analysis defines a unique cluster in approximately 10% of PwMS who share an autoantibody signature against a common motif that has similarity with many human pathogens. These patients exhibit antibody reactivity years before developing MS symptoms and have higher levels of serum neurofilament light (sNfL) compared to other PwMS. Furthermore, this profile is preserved over time, providing molecular evidence for an immunologically active preclinical period years before clinical onset. This autoantibody reactivity was validated in samples from a separate incident MS cohort in both cerebrospinal fluid and serum, where it is highly specific for patients eventually diagnosed with MS. This signature is a starting point for further immunological characterization of this MS patient subset and may be clinically useful as an antigen-specific biomarker for high-risk patients with clinically or radiologically isolated neuroinflammatory syndromes.
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Autoanticuerpos , Esclerosis Múltiple , Proteínas de Neurofilamentos , Humanos , Esclerosis Múltiple/inmunología , Esclerosis Múltiple/sangre , Autoanticuerpos/sangre , Autoanticuerpos/inmunología , Proteínas de Neurofilamentos/sangre , Proteínas de Neurofilamentos/inmunología , Biomarcadores/sangre , Estudios de Cohortes , Femenino , Masculino , Adulto , Persona de Mediana EdadRESUMEN
BACKGROUND: People living with multiple sclerosis (MS) face a higher likelihood of being diagnosed with a depressive disorder than the general population. Although many low-cost screening tools and evidence-based interventions exist, depression in people living with MS is underreported, underascertained by clinicians, and undertreated. OBJECTIVE: This study aims to design a closed-loop tool to improve depression care for these patients. It would support regular depression screening, tie into the point of care, and support shared decision-making and comprehensive follow-up. After an initial development phase, this study involved a proof-of-concept pilot randomized controlled trial (RCT) validation phase and a detailed human-centered design (HCD) phase. METHODS: During the initial development phase, the technological infrastructure of a clinician-facing point-of-care clinical dashboard for MS management (BRIDGE) was leveraged to incorporate features that would support depression screening and comprehensive care (Care Technology to Ascertain, Treat, and Engage the Community to Heal Depression in people living with MS [MS CATCH]). This linked a patient survey, in-basket messages, and a clinician dashboard. During the pilot RCT phase, a convenience sample of 50 adults with MS was recruited from a single MS center with 9-item Patient Health Questionnaire scores of 5-19 (mild to moderately severe depression). During the routine MS visit, their clinicians were either asked or not to use MS CATCH to review their scores and care outcomes were collected. During the HCD phase, the MS CATCH components were iteratively modified based on feedback from stakeholders: people living with MS, MS clinicians, and interprofessional experts. RESULTS: MS CATCH links 3 features designed to support mood reporting and ascertainment, comprehensive evidence-based management, and clinician and patient self-management behaviors likely to lead to sustained depression relief. In the pilot RCT (n=50 visits), visits in which the clinician was randomized to use MS CATCH had more notes documenting a discussion of depressive symptoms than those in which MS CATCH was not used (75% vs 34.6%; χ21=8.2; P=.004). During the HCD phase, 45 people living with MS, clinicians, and other experts participated in the design and refinement. The final testing round included 20 people living with MS and 10 clinicians including 5 not affiliated with our health system. Most scoring targets for likeability and usability, including perceived ease of use and perceived effectiveness, were met. Net Promoter Scale was 50 for patients and 40 for clinicians. CONCLUSIONS: Created with extensive stakeholder feedback, MS CATCH is a closed-loop system aimed to increase communication about depression between people living with MS and their clinicians, and ultimately improve depression care. The pilot findings showed evidence of enhanced communication. Stakeholders also advised on trial design features of a full year long Department of Defense-funded feasibility and efficacy trial, which is now underway. TRIAL REGISTRATION: ClinicalTrials.gov NCT05865405; http://tinyurl.com/4zkvru9x.
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The quantum supremacy experiment, such as Google Sycamore [F. Arute et al., Nature (London) 574, 505 (2019).NATUAS0028-083610.1038/s41586-019-1666-5], poses a great challenge for classical verification due to the exponentially increasing compute cost. Using a new-generation Sunway supercomputer within 8.5 d, we provide a direct verification by computing 3×10^{6} exact amplitudes for the experimentally generated bitstrings, obtaining a cross-entropy benchmarking fidelity of 0.191% (the estimated value is 0.224%). The leap of simulation capability is built on a multiple-amplitude tensor network contraction algorithm which systematically exploits the "classical advantage" (the inherent "store-and-compute" operation mode of von Neumann machines) of current supercomputers, and a fused tensor network contraction algorithm which drastically increases the compute efficiency on heterogeneous architectures. Our method has a far-reaching impact in solving quantum many-body problems, statistical problems, as well as combinatorial optimization problems.
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INTRODUCTION: Depression occurs in over 50% of individuals living with multiple sclerosis (MS) and can be treated using many modalities. Yet, it remains: under-reported by patients, under-ascertained by clinicians and under-treated. To enhance these three behaviours likely to promote evidence-based depression care, we engaged multiple stakeholders to iteratively design a first-in-kind digital health tool. The tool, MS CATCH (Care technology to Ascertain, Treat, and engage the Community to Heal depression in patients with MS), closes the communication loop between patients and clinicians. Between clinical visits, the tool queries patients monthly about mood symptoms, supports patient self-management and alerts clinicians to worsening mood via their electronic health record in-basket. Clinicians can also access an MS CATCH dashboard displaying patients' mood scores over the course of their disease, and providing comprehensive management tools (contributing factors, antidepressant pathway, resources in patient's neighbourhood). The goal of the current trial is to evaluate the clinical effect and usability of MS CATCH in a real-world clinical setting. METHODS AND ANALYSIS: MS CATCH is a single-site, phase II randomised, delayed start, trial enrolling 125 adults with MS and mild to moderately severe depression. Arm 1 will receive MS CATCH for 12 months, and arm 2 will receive usual care for 6 months, then MS CATCH for 6 months. Clinicians will be randomised to avoid practice effects. The effectiveness analysis is superiority intent-to-treat comparing MS CATCH to usual care over 6 months (primary outcome: evidence of screening and treatment; secondary outcome: Hospital Anxiety Depression Scale-Depression scores). The usability of the intervention will also be evaluated (primary outcome: adoption; secondary outcomes: adherence, engagement, satisfaction). ETHICS AND DISSEMINATION: University of California, San Francisco Institutional Review Board (22-36620). The findings of the study are planned to be shared through conferences and publishments in a peer-reviewed journal. The deidentified dataset will be shared with qualified collaborators on request, provision of CITI and other certifications, and data sharing agreement. We will share the results, once the data are complete and analysed, with the scientific community and patient/clinician participants through abstracts, presentations and manuscripts. TRIAL REGISTRATION NUMBER: NCT05865405.
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Depresión , Esclerosis Múltiple , Adulto , Humanos , Antidepresivos/uso terapéutico , Ansiedad/prevención & control , Ensayos Clínicos Fase II como Asunto , Depresión/prevención & control , Esclerosis Múltiple/complicaciones , Esclerosis Múltiple/terapia , San Francisco , Ensayos Clínicos Pragmáticos como Asunto , Ensayos Clínicos Controlados Aleatorios como AsuntoRESUMEN
BACKGROUND: The dynamic interaction between cancer cells and tumour-associated macrophages (TAMs) in the hypoxic tumour microenvironment (TME) is an active barrier to the effector arm of the antitumour immune response. Cancer-secreted exosomes are emerging mediators of this cancer-stromal cross-talk in the TME; however, the mechanisms underlying this interaction remain unclear. METHODS: Exosomes were isolated with ExoQuick exosome precipitation solution. The polarizing effect of TAMs was evaluated by flow cytometry, western blot analysis, immunofluorescence staining and in vitro phagocytosis assays. Clinical cervical cancer specimens and an in vivo xenograft model were also employed. RESULTS: Our previous study showed that hypoxia increased the expression of ZEB1 in cervical squamous cell carcinoma (CSCC) cells, which resulted in increased infiltration of TAMs. Here, we found that hypoxia-induced ZEB1 expression is closely correlated with CD47-SIRPα axis activity in CSCC, which enables cancer cells to evade phagocytosis by macrophages and promotes tumour progression. ZEB1 was found to directly activate the transcription of the CD47 gene in hypoxic CSCC cells. We further showed that endogenous ZEB1 was characteristically enriched in hypoxic CSCC cell-derived exosomes and transferred into macrophages via these exosomes to promote SIRPα+ TAM polarization. Intriguingly, exosomal ZEB1 retained transcriptional activity and reprogrammed SIRPα+ TAMs via activation of the STAT3 signalling pathway in vitro and in vivo. STAT3 inhibition reduced the polarizing effect induced by exosomal ZEB1. Knockdown of ZEB1 increased the phagocytosis of CSCC cells by macrophages via decreasing CD47 and SIRPα expression. CONCLUSIONS: Our results suggest that hypoxia-induced ZEB1 promotes immune evasion in CSCC by strengthening the CD47-SIRPα axis. ZEB1-targeted therapy in combination with CD47-SIRPα checkpoint immunotherapy may improve the outcomes of CSCC patients in part by disinhibiting innate immunity.
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Carcinoma de Células Escamosas , Escape del Tumor , Neoplasias del Cuello Uterino , Homeobox 1 de Unión a la E-Box con Dedos de Zinc , Femenino , Humanos , Antígeno CD47 , Exosomas , Evasión Inmune , Microambiente Tumoral , Neoplasias del Cuello Uterino/metabolismo , Homeobox 1 de Unión a la E-Box con Dedos de Zinc/metabolismoRESUMEN
BACKGROUND: Falls are common in people with multiple sclerosis (MS), causing injuries, fear of falling, and loss of independence. Although targeted interventions (physical therapy) can help, patients underreport and clinicians undertreat this issue. Patient-generated data, combined with clinical data, can support the prediction of falls and lead to timely intervention (including referral to specialized physical therapy). To be actionable, such data must be efficiently delivered to clinicians, with care customized to the patient's specific context. OBJECTIVE: This study aims to describe the iterative process of the design and development of Multiple Sclerosis Falls InsightTrack (MS-FIT), identifying the clinical and technological features of this closed-loop app designed to support streamlined falls reporting, timely falls evaluation, and comprehensive and sustained falls prevention efforts. METHODS: Stakeholders were engaged in a double diamond process of human-centered design to ensure that technological features aligned with users' needs. Patient and clinician interviews were designed to elicit insight around ability blockers and boosters using the capability, opportunity, motivation, and behavior (COM-B) framework to facilitate subsequent mapping to the Behavior Change Wheel. To support generalizability, patients and experts from other clinical conditions associated with falls (geriatrics, orthopedics, and Parkinson disease) were also engaged. Designs were iterated based on each round of feedback, and final mock-ups were tested during routine clinical visits. RESULTS: A sample of 30 patients and 14 clinicians provided at least 1 round of feedback. To support falls reporting, patients favored a simple biweekly survey built using REDCap (Research Electronic Data Capture; Vanderbilt University) to support bring-your-own-device accessibility-with optional additional context (the severity and location of falls). To support the evaluation and prevention of falls, clinicians favored a clinical dashboard featuring several key visualization widgets: a longitudinal falls display coded by the time of data capture, severity, and context; a comprehensive, multidisciplinary, and evidence-based checklist of actions intended to evaluate and prevent falls; and MS resources local to a patient's community. In-basket messaging alerts clinicians of severe falls. The tool scored highly for usability, likability, usefulness, and perceived effectiveness (based on the Health IT Usability Evaluation Model scoring). CONCLUSIONS: To our knowledge, this is the first falls app designed using human-centered design to prioritize behavior change and, while being accessible at home for patients, to deliver actionable data to clinicians at the point of care. MS-FIT streamlines data delivery to clinicians via an electronic health record-embedded window, aligning with the 5 rights approach. Leveraging MS-FIT for data processing and algorithms minimizes clinician load while boosting care quality. Our innovation seamlessly integrates real-world patient-generated data as well as clinical and community-level factors, empowering self-care and addressing the impact of falls in people with MS. Preliminary findings indicate wider relevance, extending to other neurological conditions associated with falls and their consequences.
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Accidentes por Caídas , Geriatría , Aplicaciones Móviles , Esclerosis Múltiple , Humanos , Accidentes por Caídas/prevención & control , Miedo , Esclerosis Múltiple/terapiaRESUMEN
BACKGROUND: Transplacental-derived anti-D IgG in RhD-negative pregnant women can trigger an immune response to Rh D-positive red cells in fetuses and newborns. We assessed the effect of anti-D titers in RhD-negative pregnant women on fetuses and newborns. METHODS: The clinical data of 142 singleton RhD-sensitized pregnancies were retrospectively collected. The pregnant women received routine prenatal care and the newborns had standard care. Based on the tertile categories of the pregnancies, the maximum titers of anti-D IgG in the pregnant women were divided into three groups ranging from low to high as follows: low-titer group (anti-D titer: 1:4-1:128, n = 57); medium-titer group (anti-D titer: 1:256-1:512, n = 50); and high-titer group (anti-D titer: 1:1024-1:4096, n = 35). RESULTS: The frequencies of major neonatal complications did not significantly differ among the three groups. The high-titer group had the highest frequency of pregnancies requiring intrauterine transfusion (IUT) and number of IUTs among the three groups. The high-titer group had a significantly higher frequency of newborns treated with top-up transfusion, number of top-up transfusions, frequency of newborns treated with exchange transfusion (ET), and number of ETs when compared to the low-titer group. CONCLUSION: Higher anti-D titers in RhD-negative pregnant women predict more severe fetal and neonatal hemolytic anemia. Increasing maternal anti-D titers results in an increased need for IUTs, and neonatal top-up transfusions and ETs. Methods for reducing titers of anti-D IgG in RhD-sensitized pregnant women warrants further investigation.
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BACKGROUND: Race and ancestry influence the course of multiple sclerosis (MS). OBJECTIVES: Explore clinical characteristics of MS and neuromyelitis optica spectrum disorder (NMOSD) in Asian American patients. METHODS: Chart review was performed for 282 adults with demyelinating disease who self-identified as Asian at a single North American MS center. Demographics and clinical characteristics were compared to non-Asian MS patients and by region of Asian ancestry. RESULTS: Region of ancestry was known for 181 patients. Most (94.7%) preferred English, but fewer East Asian patients did (80%, p = 0.0001). South Asian patients had higher neighborhood household income (p = 0.002). Diagnoses included MS (76.2%) and NMOSD (13.8%). More patients with NMOSD than MS were East and Southeast Asian (p = 0.004). For MS patients, optic nerve and spinal cord involvement were similar across regions of ancestry. Asian MS patients were younger at symptom onset and diagnosis than non-Asian MS patients. MS Severity Scale scores were similar to non-Asian MS patients but worse among Southeast Asians (p = 0.006). CONCLUSIONS: MS severity was similar between Asian American patients and non-Asian patients. Region of ancestry was associated with differences in sociodemographics and MS severity. Further research is needed to uncover genetic, socioeconomic, or environmental factors causing these differences.
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Esclerosis Múltiple , Neuromielitis Óptica , Adulto , Humanos , Acuaporina 4 , Asiático , Esclerosis Múltiple/epidemiología , Neuromielitis Óptica/epidemiología , Nervio ÓpticoRESUMEN
BACKGROUND: Endothelial-mesenchymal transition (EndoMT) is an emerging adaptive process that modulates lymphatic endothelial function to drive aberrant lymphatic vascularization in the tumour microenvironment (TME); however, the molecular determinants that govern the functional role of EndoMT remain unclear. Here, we show that cancer-associated fibroblast (CAF)-derived PAI-1 promoted the EndoMT of lymphatic endothelial cells (LECs) in cervical squamous cell carcinoma (CSCC). METHODS: Immunofluorescent staining of α-SMA, LYVE-1 and DAPI were examined in primary tumour samples obtained from 57 CSCC patients. Assessment of cytokines secreted by CAFs and normal fibroblasts (NFs) was performed using human cytokine antibody arrays. The phenotype of EndoMT in lymphatic endothelial cells (LECs), gene expression levels, protein secretion and activity of signaling pathways were measured by real-time RT-PCR, ELISA or western blotting. The function of lymphatic endothelial monolayers was examined by transwell, tube formation assay, transendothelial migration assay in vitro. Lymphatic metastasis was measured using popliteal lymph node metastasis model. Furthermore, association between PAI-1 expression and EndoMT in CSCC was analyzed by immunohistochemistry. The Cancer Genome Atlas (TCGA) databases was used to assess the association of PAI-1 with survival rate in CSCC. RESULTS: CAF-derived PAI-1 promoted the EndoMT of LECs in CSCC. LECs undergoing EndoMT could initiate tumour neolymphangiogenesis that facilitated cancer cell intravasation/extravasation, which in turn promoted lymphatic metastasis in CSCC. Mechanistically, PAI-1 activated the AKT/ERK1/2 pathways by directly interacting with low-density lipoprotein receptor-related protein (LRP1), thereby leading to elevated EndoMT activity in LECs. Blockade of PAI-1 or inhibition of LRP1/AKT/ERK1/2 abrogated EndoMT and consequently attenuated CAF-induced tumour neolymphangiogenesis. Furthermore, clinical data revealed that increased PAI-1 levels positively correlated with EndoMT activity and poor prognosis in CSCC patients. CONCLUSION: Our data indicate that CAF-derived PAI-1 acts as an important neolymphangiogenesis-initiating molecular during CSCC progression through modulating the EndoMT of LECs, resulting in promotion of metastasis ability in primary site. PAI-1 could serve as an effective prognostic biomarker and therapeutic target for CSCC metastasis.
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Fibroblastos Asociados al Cáncer , Células Endoteliales , Femenino , Humanos , Movimiento Celular/genética , Células Endoteliales/metabolismo , Metástasis Linfática , Inhibidor 1 de Activador Plasminogénico/genética , Inhibidor 1 de Activador Plasminogénico/metabolismo , Proteínas Proto-Oncogénicas c-akt/metabolismo , Microambiente TumoralRESUMEN
Although B cells are implicated in multiple sclerosis (MS) pathophysiology, a predictive or diagnostic autoantibody remains elusive. Here, the Department of Defense Serum Repository (DoDSR), a cohort of over 10 million individuals, was used to generate whole-proteome autoantibody profiles of hundreds of patients with MS (PwMS) years before and subsequently after MS onset. This analysis defines a unique cluster of PwMS that share an autoantibody signature against a common motif that has similarity with many human pathogens. These patients exhibit antibody reactivity years before developing MS symptoms and have higher levels of serum neurofilament light (sNfL) compared to other PwMS. Furthermore, this profile is preserved over time, providing molecular evidence for an immunologically active prodromal period years before clinical onset. This autoantibody reactivity was validated in samples from a separate incident MS cohort in both cerebrospinal fluid (CSF) and serum, where it is highly specific for patients eventually diagnosed with MS. This signature is a starting point for further immunological characterization of this MS patient subset and may be clinically useful as an antigen-specific biomarker for high-risk patients with clinically- or radiologically-isolated neuroinflammatory syndromes.
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Classifying many-body quantum states with distinct properties and phases of matter is one of the most fundamental tasks in quantum many-body physics. However, due to the exponential complexity that emerges from the enormous numbers of interacting particles, classifying large-scale quantum states has been extremely challenging for classical approaches. Here, we propose a new approach called quantum neuronal sensing. Utilizing a 61-qubit superconducting quantum processor, we show that our scheme can efficiently classify two different types of many-body phenomena: namely the ergodic and localized phases of matter. Our quantum neuronal sensing process allows us to extract the necessary information coming from the statistical characteristics of the eigenspectrum to distinguish these phases of matter by measuring only one qubit and offers better phase resolution than conventional methods, such as measuring the imbalance. Our work demonstrates the feasibility and scalability of quantum neuronal sensing for near-term quantum processors and opens new avenues for exploring quantum many-body phenomena in larger-scale systems.
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Quantum computing is moving beyond its early stage and seeking for commercial applications in chemical and biomedical sciences. In the current noisy intermediate-scale quantum computing era, the quantum resource is too scarce to support these explorations. Therefore, it is valuable to emulate quantum computing on classical computers for developing quantum algorithms and validating quantum hardware. However, existing simulators mostly suffer from the memory bottleneck so developing the approaches for large-scale quantum chemistry calculations remains challenging. Here we demonstrate a high-performance and massively parallel variational quantum eigensolver (VQE) simulator based on matrix product states, combined with embedding theory for solving large-scale quantum computing emulation for quantum chemistry on HPC platforms. We apply this method to study the torsional barrier of ethane and the quantification of the protein-ligand interactions. Our largest simulation reaches 1000 qubits, and a performance of 216.9 PFLOP/s is achieved on a new Sunway supercomputer, which sets the state-of-the-art for quantum computing emulation for quantum chemistry.
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BACKGROUND AND OBJECTIVES: Prospective, deeply phenotyped research cohorts monitoring individuals with chronic neurologic conditions, such as multiple sclerosis (MS), depend on continued participant engagement. The COVID-19 pandemic restricted in-clinic research activities, threatening this longitudinal engagement, but also forced adoption of televideo-enabled care. This offered a natural experiment in which to analyze key dimensions of remote research: (1) comparison of remote vs in-clinic visit costs from multiple perspectives and (2) comparison of the remote with in-clinic measures in cross-sectional and longitudinal disability evaluations. METHODS: Between March 2020 and December 2021, 207 MS cohort participants underwent hybrid in-clinic and virtual research visits; 96 contributed 100 "matched visits," that is, in-clinic (Neurostatus-Expanded Disability Status Scale [NS-EDSS]) and remote (televideo-enabled EDSS [tele-EDSS]; electronic patient-reported EDSS [ePR-EDSS]) evaluations. Clinical, demographic, and socioeconomic characteristics of participants were collected. RESULTS: The costs of remote visits were lower than in-clinic visits for research investigators (facilities, personnel, parking, participant compensation) but also for participants (travel, caregiver time) and carbon footprint (p < 0.05 for each). Median cohort EDSS was similar between the 3 modalities (NS-EDSS: 2, tele-EDSS: 1.5, ePR-EDSS: 2, range 0.6.5); the remote evaluations were each noninferior to the NS-EDSS within ±0.5 EDSS point (TOST for noninferiority, p < 0.01 for each). Furthermore, year to year, the % of participants with worsening/stable/improved EDSS scores was similar, whether each annual evaluation used NS-EDSS or whether it switched from NS-EDSS to tele-EDSS. DISCUSSION: Altogether, the current findings suggest that remote evaluations can reduce the costs of research participation for patients, while providing a reasonable evaluation of disability trajectory longitudinally. This could inform the design of remote research that is more inclusive of diverse participants.
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COVID-19 , Esclerosis Múltiple , Humanos , Estudios Prospectivos , Estudios Transversales , PandemiasRESUMEN
Conventional theoretical studies on the ground-state laser cooling of a trapped ion have mostly focused on the weak sideband coupling (WSC) regime, where the cooling rate is inverse proportional to the linewidth of the excited state. In a recent work [New J. Phys.23, 023018 (2021)10.1088/1367-2630/abe273], we proposed a theoretical framework to study the ground state cooling of a trapped ion in the strong sideband coupling (SSC) regime, under the assumption of a vanishing carrier transition. Here we extend this analysis to more general situations with nonvanishing carrier transitions, where we show that by properly tuning the coupling lasers a cooling rate proportional to the linewidth can be achieved. Our theoretical predictions closely agree with the corresponding exact solutions in the SSC regime, which provide an important theoretical guidance for sideband cooling experiments.
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To ensure a long-term quantum computational advantage, the quantum hardware should be upgraded to withstand the competition of continuously improved classical algorithms and hardwares. Here, we demonstrate a superconducting quantum computing systems Zuchongzhi 2.1, which has 66 qubits in a two-dimensional array in a tunable coupler architecture. The readout fidelity of Zuchongzhi 2.1 is considerably improved to an average of 97.74%. The more powerful quantum processor enables us to achieve larger-scale random quantum circuit sampling, with a system scale of up to 60 qubits and 24 cycles, and fidelity of FXEB=(3.66±0.345)×10-4. The achieved sampling task is about 6 orders of magnitude more difficult than that of Sycamore [Nature 574, 505 (2019)] in the classic simulation, and 3 orders of magnitude more difficult than the sampling task on Zuchongzhi 2.0 [arXiv:2106.14734 (2021)]. The time consumption of classically simulating random circuit sampling experiment using state-of-the-art classical algorithm and supercomputer is extended to tens of thousands of years (about 4.8×104 years), while Zuchongzhi 2.1 only takes about 4.2 h, thereby significantly enhancing the quantum computational advantage.
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OBJECTIVES: To evaluate the early risk factors for death in neonates with persistent pulmonary hypertension of the newborn (PPHN) treated with inhaled nitric oxide (iNO). METHODS: A retrospective analysis was performed on 105 infants with PPHN (gestational age ≥34 weeks and age <7 days on admission) who received iNO treatment in the Department of Neonatology, Children's Hospital of Nanjing Medical University, from July 2017 to March 2021. Related general information and clinical data were collected. According to the clinical outcome at discharge, the infants were divided into a survival group with 79 infants and a death group with 26 infants. Univariate and multivariate Cox regression analyses were used to evaluate the risk factors for death in infants with PPHN treated with iNO. The receiver operating characteristic (ROC) curve was used to calculate the cut-off values of the factors in predicting the death risk. RESULTS: A total of 105 infants with PPHN treated with iNO were included, among whom 26 died (26/105, 24.8%). The multivariate Cox regression analysis showed that no early response to iNO (HR=8.500, 95%CI: 3.024-23.887, P<0.001), 1-minute Apgar score ≤3 points (HR=10.094, 95%CI: 2.577-39.534, P=0.001), a low value of minimum PaO2/FiO2 within 12 hours after admission (HR=0.067, 95%CI: 0.009-0.481, P=0.007), and a low value of minimum pH within 12 hours after admission (HR=0.049, 95%CI: 0.004-0.545, P=0.014) were independent risk factors for death. The ROC curve analysis showed that the lowest PaO2/FiO2 value within 12 hours after admission had an area under the ROC curve of 0.783 in predicting death risk, with a sensitivity of 84.6% and a specificity of 73.4% at the cut-off value of 50, and the lowest pH value within 12 hours after admission had an area under the ROC curve of 0.746, with a sensitivity of 76.9% and a specificity of 65.8% at the cut-off value of 7.2. CONCLUSIONS: Infants with PPHN requiring iNO treatment tend to have a high mortality rate. No early response to iNO, 1-minute Apgar score ≤3 points, the lowest PaO2/FiO2 value <50 within 12 hours after admission, and the lowest pH value <7.2 within 12 hours after admission are the early risk factors for death in such infants. Monitoring and evaluation of the above indicators will help to identify high-risk infants in the early stage.