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Among existing approaches to holonomic quantum computing, the adiabatic holonomic quantum gates (HQGs) suffer errors due to decoherence, while the non-adiabatic HQGs either require additional Hilbert spaces or are difficult to scale. Here, we report a systematic, scalable approach based on dynamical invariants to realize HQGs without using additional Hilbert spaces. While presenting the theoretical framework of our approach, we design and experimentally evaluate single-qubit and two-qubits HQGs for the nuclear magnetic resonance system. The single-qubit gates acquire average fidelity 0.9972 by randomized benchmarking, and the controlled-NOT gate acquires fidelity 0.9782 by quantum process tomography. Our approach is also platform-independent, and thus may open a way to large-scale holonomic quantum computation.

Abstract Hearing impairment is a global health problem that affects social communications and the economy. The damage and loss of cochlear hair cells and spiral ganglion neurons (SGNs) as well as the degeneration of neurites of SGNs are the core causes of sensorineural hearing loss. Biotechnologies and biomedical engineering technologies provide new hope for the treatment of auditory diseases, which utilizes biological strategies or tissue engineering methods to achieve drug delivery and the regeneration of cells, tissues, and even organs. Here, the advancements in the applications of biotechnologies (including gene therapy and cochlear organoids) and biomedical engineering technologies (including drug delivery, electrode coating, electrical stimulation and bionic scaffolds) in the field of hearing reconstruction are presented. Moreover, we summarize the challenges and provide a perspective on this field.

Background: Cerebral autosomal recessive arteriopathy with subcortical infarcts and leukoencephalopathy (CARASIL) is an autosomal recessive disorder characterized by baldness, recurrent ischemic stroke, lumbago, headache, and dementia which is closely related to homozygous mutations of the high-temperature requirement serine peptidase A1 (HTRA1) gene. Heterozygous mutations of HTRA1 are usually considered to be non-pathogenic. Although it has been revealed that only a few patients with heterozygous mutations could present some manifestations, their clinical symptoms were atypical, milder, and always with a lower frequency of extra-neurological features. Here, a rare patient with heterozygous mutation of HTRA1 who had all typical features of CARASIL as well as severe clinical symptoms and rapid progression was initially reported in our study.Case presentation: A 43-year-old female patient presented with a gradual onset of headache and cognitive decline. As time progressed, her headache intensified and symptoms of dementia began to manifest gradually. During her early years, she had thinning hair and subsequently experienced two occurrences of ischemic strokes in her thirties. Furthermore, she also had a history of lumbago and urinary retention before visiting our hospital. The patient’s magnetic resonance imaging revealed the presence of widespread white matter lesions, infarctions, and microbleeds, in addition to lumbar disc herniation and degenerative lesions. The observed clinical characteristics had a strong correlation with CARASIL, and the patient was diagnosed with a heterozygous missense mutation of 905G>A (Arg302Gln) in the HTRA1 gene. The patient has been under continuous follow-up for a duration exceeding 3 years subsequent to her release from the hospital. She underwent cystostomy, and symptoms of bulbar paralysis developed in a progressive way. Currently, there has been a notable decrease in motor function and activities of daily living, resulting in the individual being confined to bed for a duration exceeding 1 year.Conclusion: This case suggests that patients carrying a heterozygous mutation in G905A may also have typical clinical features of CARASIL, which allows us to have a more comprehensive understanding of CARASIL.

Topological quantum computation (TQC) is one of the most striking architectures that can realize fault-tolerant quantum computers. In TQC, the logical space and the quantum gates are topologically protected, i.e., robust against local disturbances. The topological protection, however, requires complicated lattice models and hard-to-manipulate dynamics; even the simplest system that can realize universal TQC—the Fibonacci anyon system—lacks a physical realization, let alone braiding the non-Abelian anyons. Here, we propose a disk model that can simulate the Fibonacci anyon system and construct the topologically protected logical spaces with the Fibonacci anyons. Via braiding the Fibonacci anyons, we can implement universal quantum gates on the logical space. Our disk model merely requires two physical qubits to realize three Fibonacci anyons at the boundary. By 15 sequential braiding operations, we construct a topologically protected Hadamard gate, which is to date the least-resource requirement for TQC. To showcase, we implement a topological Hadamard gate with two nuclear spin qubits, which reaches 97.18% fidelity by randomized benchmarking. We further prove by experiment that the logical space and Hadamard gate are topologically protected: local disturbances due to thermal fluctuations result in a global phase only. As a platform-independent proposal, our work is a proof of principle of TQC and paves the way toward fault-tolerant quantum computation.

Walking detection in the daily life of patients with Parkinson’s disease (PD) is of great significance for tracking the progress of the disease. This study aims to implement an accurate, objective, and passive detection algorithm optimized based on an interpretable deep learning architecture for the daily walking of patients with PD and to explore the most representative spatiotemporal motor features. Five inertial measurement units attached to the wrist, ankle, and waist are used to collect motion data from 100 subjects during a 10-meter walking test. The raw data of each sensor are subjected to the continuous wavelet transform to train the classification model of the constructed 6-channel convolutional neural network (CNN). The results show that the sensor located at the waist has the best classification performance with an accuracy of 98.01%±0.85% and the area under the receiver operating characteristic curve (AUC) of 0.9981±0.0017 under ten-fold cross-validation. The gradient-weighted class activation mapping shows that the feature points with greater contribution to PD were concentrated in the lower frequency band (0.5~3Hz) compared with healthy controls. The visual maps of the 3D CNN show that only three out of the six time series have a greater contribution, which is used as a basis to further optimize the model input, greatly reducing the raw data processing costs (50%) while ensuring its performance (AUC=0.9929±0.0019). To the best of our knowledge, this is the first study to consider the visual interpretation-based optimization of an intelligent classification model in the intelligent diagnosis of PD.

Abstract Background To identify potential targets related to nicotinamide adenine dinucleotide (NAD+) metabolism in gliomas, we used RNA immunoprecipitation to identify a novel long noncoding RNA renamed malate dehydrogenase degradation helper (MDHDH) (NONCODE annotation ID: NONHSAT138800.2, NCBI Reference Sequence: NR_028345), which bound to MDH2 (malate dehydrogenase 2), that is downregulated in glioblastoma multiforme (GBM) and associated with metabolic regulation. However, its underlying mechanisms in the progression of GBM have not been well studied. Methods To investigate the clinical significance of MDHDH, we analyzed its expression levels in publicly available datasets and collected clinical samples from Shandong Provincial Hospital, affiliated with Shandong University. Functional assays, including FISH/CISH, CCK8, EdU, wound healing, and transwell assays, were used to determine the cellular/subcellular localization, tissue expression profile and anti-oncogenic role of MDHDH. Furthermore, RNA pulldown, mass spectrometry RNA immunoprecipitation, coimmunoprecipitation, JC-1 probe, and cell energy-production assays were used to determine the mechanisms of MDHDH in the development of GBM. Animal experiments were conducted to determine the antitumorigenic role of MDHDH in GBM in vivo. Results In public datasets, MDHDH expression was significantly downregulated in GBM and LGG compared with GTEx normal brain tissues. The results of the tissue microarray showed that the MDHDH expression level negatively correlated with the tumor grade. Altered MDHDH expression led to significant changes in the proliferation, migration and invasion of GBM cells both in vitro and in vivo. Mechanistically, we found that MDHDH directly bound to MDH2 and PSMA1 (20S proteasomal core subunit alpha-type 1) as a molecular scaffold and accelerated the degradation of MDH2 by promoting the binding of ubiquitinated MDH2 to the proteasome. The degradation of MDH2 subsequently led to changes in the mitochondrial membrane potential and NAD+/NADH ratio, which impeded glycolysis in glioma cells. Conclusions In conclusion, this study broadened our understanding of the functions of lncRNAs in GBM. We demonstrated that the tumor suppressor MDHDH might act as a clinical biomarker and that the overexpression of MDHDH might be a novel synergistic strategy for enhancing metabolism-based, epigenetic-based, and autophagy regulation-based therapies with clinical benefits for glioblastoma multiforme patients.

Background and objective In advanced non-small cell lung cancer (NSCLC), leptomeningeal metastases (LM) is a common consequence with rapid progression and a poor prognosis. LM affects roughly 3% to 5% of NSCLC patients, and it affects as many as 9.4% of individuals with epidermal growth factor receptor (EGFR) mutations. Cerebrospinal fluid cytology is the gold standard for diagnosing LM, while conventional cytopathology has a positive detection rate of less than 50%, resulting in a delay in diagnosis and treatment of LM. The fixation treatment of cerebrospinal fluid samples has a significant impact on the positive cytology detection rate, and how to improve the positive cytopathology detection rate of cerebrospinal fluid is a hot topic in clinical research. Methods From June 2019 to November 2021, 105 cases diagnosed with LM based on clinical symptoms and positive imaging were collected and retrospectively evaluated in the second ward of the Department of Oncology of The Second Affiliated Hospital of Harbin Medical University. The effect of different fixation methods on the positive rate of cerebrospinal fluid cytopathology was investigated, and specimens of cerebrospinal fluid were collected and sent for examination using different delivery methods, including the application of the TIB cell preservation solution kit (experimental group) and the routine application of sterile plastic tubes in lumbar puncture bags (control group). Biochemical assays (glucose and total protein) were performed on the cerebrospinal fluid fluid, and Logistic regression analysis and receiver operating characteristic (ROC) curve were used to evaluate the supplementary diagnostic value for LM patients with lung cancer. The relevance of chemical indexes in the assessment of therapeutic efficacy was examined, and biochemical (glucose, total protein) indices and cytological changes in cerebrospinal fluid fluid after pemetrexed intrathecal injection therapy were dynamically monitored. Results In the control group, 24 (45.28%) patients were positive for the first time, while 42 (80.77%) patients were positive for the first time and 10 (19.23%) patients were negative for the first time in the experimental group. Significant differences existed between the two groups (P0.05). The ROC curve showed glucose sensitivity of 76.9% in cerebrospinal fluid, the specificity of 54.5%, Youden index of 0.315 and area under the curve (AUC) of 0.620, total protein sensitivity in cerebrospinal fluid of 44.4%, 90.6%, Youden index of 0.350 and AUC of 0.671. After 2 cycles of pemetrexed intrathecal treatment with complete cerebrospinal fluid cytology and cerebrospinal fluid biochemical (glucose, total protein) tests in 73 and 50 patients, respectively, the rate of cerebrospinal fluid cytology turning negative was gradually increased. Cerebrospinal fluid glucose levels increased after 2 cycles of treatment compared with the first time, with a statistically significant difference (P

Abstract Background Endovascular treatment (EVT) for acute ischemic stroke with an occlusion of the M1 segment due to intracranial atherosclerotic severe stenosis (ICASS) remains challenging. This study aimed to evaluate the safety and efficacy of EVT for ICASS-related M1 acute occlusion. Methods We retrospectively reviewed all patients with an ICASS-related M1 acute occlusion who underwent EVT at our institution between January 2015 and December 2020. Clinical presentation, baseline characteristics, angiographic and clinical results, technical feasibility, perioperative complications, and follow-up results were evaluated. Results Twenty-two patients with ICASS-related M1 acute occlusion were included. Eight patients (36.4%) received bridging therapy, and the other 14 patients (63.6%) directly underwent EVT. Fifteen patients (68.2%) treated with balloon dilations and stenting as rescue treatment. Six patients (27.3%) received single balloon angioplasty, and 5 of these patients were treated with staged stenting. One case (4.5%) failed recanalization at the first EVT, and successful revascularization was achieved a month later. The mean procedure time was 67.2 ± 20.8 min. Successful revascularization (mTICI ≥ 2b) was achieved in 95.5% (21/22) of patients. Perioperative complications developed in two patients (9.1%) including one hemorrhagic event and one thromboembolic event. Angiographic follow-up was available in 20 patients (90.9%) at an average of 8.6 ± 3.0 months. The degree of stenosis was worse (10–30%) in 6 cases (30%) compared with the initial outcomes. The favorable outcomes (mRS ≤ 2) at 3-month follow-up was achieved in 19 patients (86.4%). Conclusions ICASS-related occlusion in the M1 segment often required a rescue therapy including balloon angioplasty with/without stenting, and this treatment strategy was safe and effective. But single balloon angioplasty at the first EVT generally cannot achieve satisfactory results and often needed staged stenting treatment.

Eigensolvers have a wide range of applications in machine learning. Quantum eigensolvers have been developed for achieving quantum speedup. Here, we propose a parallel quantum eigensolver (PQE) for solving a set of machine learning problems, which is based on quantum multi-resonant transitions that simultaneously trigger multiple energy transitions in the systems on demand. PQE has a polylogarithmic cost in problem size under certain circumstances and is hardware efficient, such that it is implementable in near-term quantum computers. As a verification, we utilize it to construct a collaborative filtering quantum recommendation system and implement an experiment of the movie recommendation tasks on a nuclear spin quantum processor. As a result, our recommendation system accurately suggests movies to the user that he/she might be interested in. We further demonstrate the applications of PQE in classification and image completion. In the future, our work will shed light on more applications in quantum machine learning.

Computer-based assessments provide the opportunity to collect a new source of behavioral data related to the problem-solving process, known as log file data. To understand the behavioral patterns that can be uncovered from these process data, many studies have employed clustering methods. In contrast to one-mode clustering algorithms, this study utilized biclustering methods, enabling simultaneous classification of test takers and features extracted from log files. By applying the biclustering algorithms to the “Ticket” task in the PISA 2012 CPS assessment, we evaluated the potential of biclustering algorithms in identifying and interpreting homogeneous biclusters from the process data. Compared with one-mode clustering algorithms, the biclustering methods could uncover clusters of individuals who are homogeneous on a subset of feature variables, holding promise for gaining fine-grained insights into students’ problem-solving behavior patterns. Empirical results revealed that specific subsets of features played a crucial role in identifying biclusters. Additionally, the study explored the utilization of biclustering on both the action sequence data and timing data, and the inclusion of time-based features enhanced the understanding of students’ action sequences and scores in the context of the analysis.

Leptomeningeal metastases (LM), a special type of metastasis in advanced lung cancer, is known for its severe clinical symptoms, rapid progression and poor prognosis. LM used to be featured with low clinical diagnosis rate, limited treatment options, poor treatment efficacy, and very short survival if treatment not given. Though cerebrospinal fluid (CSF) cytology remains to be the gold standard for the diagnosis of LM, the positive rate of the first CSF cytology even in patients with suggestive clinical symptoms and positive imaging generally does not exceed 50%, leading to a delay in the diagnosis and treatment of patients with LM. With the progress of targeted therapy for driver gene-positive lung cancer and immunotherapy for driver gene-negative lung cancer, the overall survival of patients with lung cancer has been prolonged, meanwhile incidence of LM has been increasing year by year. Current clinical research in this field center around how to improve diagnosis rate and to find effective treatment approaches. This paper reviews advances in diagnosis and treatment of LM of lung cancer..

Abstract Noise is ubiquitous in real quantum systems, leading to non-Hermitian quantum dynamics, and may affect the fundamental states of matter. Here we report in an experiment a quantum simulation of the two-dimensional non-Hermitian quantum anomalous Hall (QAH) model using the nuclear magnetic resonance processor. Unlike the usual experiments using auxiliary qubits, we develop a stochastic average approach based on the stochastic Schrödinger equation to realize the non-Hermitian dissipative quantum dynamics, which has advantages in saving the quantum simulation sources and simplifying the implementation of quantum gates. We demonstrate the stability of dynamical topology against weak noise and observe two types of dynamical topological transitions driven by strong noise. Moreover, a region where the emergent topology is always robust regardless of the noise strength is observed. Our work shows a feasible quantum simulation approach for dissipative quantum dynamics with stochastic Schrödinger equation and opens a route to investigate non-Hermitian dynamical topological physics.

Glioblastoma is acknowledged as the most aggressive cerebral tumor in adults. However, the efficacy of current standard therapy is seriously undermined by drug resistance and suppressive immune microenvironment. Ferroptosis is a recently discovered form of iron-dependent cell death that may have excellent prospect as chemosensitizer. The utilization of ferropotosis inducer Erastin could significantly mediate chemotherapy sensitization of Temozolomide and exert anti-tumor effects in glioblastoma. In this study, a combination of hydrogel-liposome nanoplatform encapsulated with Temozolomide and ferroptosis inducer Erastin was constructed. The αvβ3 integrin-binding peptide cyclic RGD was utilized to modify codelivery system to achieve glioblastoma targeting strategy. As biocompatible drug reservoirs, cross-linked GelMA (gelatin methacrylamide) hydrogel and cRGD-coated liposome realized the sustained release of internal contents. In the modified intracranial tumor resection model, GelMA-liposome system achieved slow release of Temozolomide and Erastin in situ for more than 14 d. The results indicated that nanoplatform (T+E@LPs-cRGD+GelMA) improved glioblastoma sensitivity to chemotherapeutic temozolomide and exerted satisfactory anti-tumor effects. It was demonstrated that the induction of ferroptosis could be utilized as a therapeutic strategy to overcome drug resistance. Furthermore, transcriptome sequencing was conducted to reveal the underlying mechanism that the nanoplatform (T+E@LPs-cRGD+GelMA) implicated in. It is suggested that GelMA-liposome system participated in the immune response and immunomodulation of glioblastoma via interferon/PD-L1 pathway. Collectively, this study proposed a potential combinatory therapeutic strategy for glioblastoma treatment.

ObjectiveTo evaluate the efficacy and safety of combined traditional Chinese medicine in the adjuvant treatment of proliferative diabetic retinopathy (PDR) by Meta-analysis.MethodsPubMed, Embase, Web of Science, Cochrane Library, China National Knowledge Infrastructure (CNKI), Wanfang databases were searched by computer. Random controlled clinical trials (RCTS) using traditional Chinese medicine as adjuvant therapy for proliferative diabetic retinopathy were screened, and Stata16.0 software was used to perform meta-analysis on the final included literatures.ResultsA total of 18 studies involving 1392 patients were included. Meta-analysis showed that the clinical effective rate OR=2.99 (CI: 2.18-4.10, I2 = 42.7%, P