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Carbohydrate digestibility is a key determinant for elevated postprandial hyperglycemia (PPHG). Apart from dietary restrictions, one of the strategies to reduce PPHG is to limit the activity of carbohydrate digestive enzymes within the gastrointestinal tract in order to reduce monosaccharide absorption rates. The present work aimed to assess the inhibitory capabilities of digestive enzymes (e.g., α-glucosidase and α-amylase) by anthoxanthins when used independently, in combination with acarbose, or with a different anthoxanthin. Our results showed that quercetin, myricetin, and luteolin presented lower IC50 values than acarbose and inhibited α-glucosidase through mixed-type inhibition. On the other hand, acarbose when compared with these anthoxanthins, remained the most potent inhibitor of α-amylase. Combinatorial treatment (i) acarbose-quercetin and (ii) myricetin-luteolin showed synergistic activity (CI value less than 0.9) in α-glucosidase inhibition. An additive effect (CI value between 0.9 and 1.1) in α-glucosidase inhibition was observed when acarbose-myricetin, acarbose-luteolin or when a combination of two different anthoxanthins (quercetin-myricetin and quercetin-luteolin) was used. This study suggests the potential use of anthoxanthins as functional food ingredients to mitigate PPHG towards the management of T2DM.

An aptasensor for the detection of ochratoxin A (OTA) in environmental samples was developed. It displayed high sensitivity and good selectivity. Factors such as specific binding between a FAM (5-carboxyfluorescein)-labeled aptamer (f-RP) and OTA, and a magnetic property of a streptavidin magbeads-modified capture probe (bm-CP) resulted in aptasensor’s linear relationship between fluorescence intensity and the concentration of OTA. This characteristic is present at the OTA concentration ranges from 0.100 μM to 25.00 μM with a LOD (limit of detection) of 0.0690 μM. The bm-CP can be reused through melting, washing and magnetic separation, which contributes to cost reduction. In addition, the proposed method is simple and detection process is fast. The aptasensor can be used in real samples.

Standard catheter-directed thrombolysis (CDT) and thrombus aspiration are considered potentially promising approaches for reopening the embolism-related pulmonary artery in patients with pulmonary embolism (PE) with high thrombotic burden and deteriorating hemodynamics, especially in those for whom systemic thrombolysis is contraindicated or has failed. However, the constrained accessibility of dedicated catheters has impeded the potential benefits of standard CDT in developing countries. The Guidezilla guide extension catheter (GEC) with a larger diameter and extended length is widely used in challenging coronary anatomy. Nevertheless, there have been few reports on the application of the Guidezilla GEC as a novel option for patients with massive PE when dedicated catheters and surgical thrombectomy are not available. In this case report, we demonstrated that thrombus aspiration and in situ thrombolysis through the Guidezilla GEC are applicable to patients with PE in whom systemic thrombolysis is contraindicated, resulting in successful reperfusion and positive clinical outcomes.

Abstract Environment perception is one of the most critical technology of intelligent transportation systems (ITS). Motion interaction between multiple vehicles in ITS makes it important to perform multi-object tracking (MOT). However, most existing MOT algorithms follow the tracking-by-detection framework, which separates detection and tracking into two independent segments and limit the global efficiency. Recently, a few algorithms have combined feature extraction into one network; however, the tracking portion continues to rely on data association, and requires complex post-processing for life cycle management. Those methods do not combine detection and tracking efficiently. This paper presents a novel network to realize joint multi-object detection and tracking in an end-to-end manner for ITS, named as global correlation network (GCNet). Unlike most object detection methods, GCNet introduces a global correlation layer for regression of absolute size and coordinates of bounding boxes, instead of offsetting predictions. The pipeline of detection and tracking in GCNet is conceptually simple, and does not require complicated tracking strategies such as non-maximum suppression and data association. GCNet was evaluated on a multi-vehicle tracking dataset, UA-DETRAC, demonstrating promising performance compared to state-of-the-art detectors and trackers.

Research on the host responses to respiratory viruses could help develop effective interventions and therapies against the current and future pandemics from the host perspective. To explore the pathogenesis that distinguishes SARS-CoV-2 infections from other respiratory viruses, we performed a multi-cohort analysis with integrated bioinformatics and machine learning. We collected 3730 blood samples from both asymptomatic and symptomatic individuals infected with SARS-CoV-2, seasonal human coronavirus (sHCoVs), influenza virus (IFV), respiratory syncytial virus (RSV), or human rhinovirus (HRV) across 15 cohorts. First, we identified an enhanced cellular immune response but limited interferon activities in SARS-CoV-2 infection, especially in asymptomatic cases. Second, we identified a SARS-CoV-2-specific 3-gene signature (CLSPN, RBBP6, CCDC91) that was predominantly expressed by T cells, could distinguish SARS-CoV-2 infection, including Omicron, from other common respiratory viruses regardless of symptoms, and was predictive of SARS-CoV-2 infection before detectable viral RNA on RT-PCR testing in a longitude follow-up study. Thereafter, a user-friendly online tool, based on datasets collected here, was developed for querying a gene of interest across multiple viral infections. Our results not only identify a unique host response to the viral pathogenesis in SARS-CoV-2 but also provide insights into developing effective tools against viral pandemics from the host perspective.

Abstract Background CD2‐associated protein (CD2AP) is a podocyte‐associated gene and its reduced expression is associated with the development of proteinuria and glomerulosclerosis. However, few studies have focused on the correlation between the expression and prognosis of CD2AP in renal clear cell carcinoma (ccRCC). Therefore, we aimed to assess the regulation of CD2AP expression and prognostic value in ccRCC. Methods Multiple databases were employed to examine the expression of CD2AP in ccRCC. RT‐qPCR, Western Blot and immunohistochemistry were used to validate CD2AP expression in different cell lines and tissue samples. Kaplan–Meier analysis and ROC curve analysis were performed on the predictive prognostic performance of CD2AP. COX regression was used to construct CD2AP‐related prognostic models. The TIMER and TISIDB databases were used to analyze the correlation of tumor‐infiltrating immune cells with gene expression, mutations, somatic copy number variation, and immune molecules. Mass spectrometry was used to detect methylation status of the promoter CpG site of CD2AP in multiple cells. Results We found that CD2AP expression was downregulated in ccRCC and its lower expression level was correlation with worse patient prognosis, higher tumor stage and grade and distant metastasis through analysis of databases, ccRCC cell lines and clinical tissue samples. Moreover, database and mass spectrometry techniques identified and validated cg12968598 hypermethylation as one of the key reasons for the downregulation of CD2AP expression. CD2AP expression was also associated with macrophage and neutrophil infiltration. Conclusions Taken together, our results suggest that CD2AP can be used as a diagnostic and prognostic biomarker in ccRCC patients and that DNA hypermethylation plays an important role in reducing CD2AP expression.

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.

Abstract Lead halide perovskites have made remarkable progress in the field of radiation detection owing to the excellent and unique optoelectronic properties. However, the instability and the toxicity of lead‐based perovskites have greatly hindered its practical applications. Alternatively, lead‐free perovskites with high stability and environmental friendliness thus have fascinated significant research attention for direct X‐ray detection. In this review, the current research progress of X‐ray detectors based on lead‐free halide perovskites is focused. First, the synthesis methods of lead‐free perovskites including single crystals and films are discussed. In addition, the properties of these materials and the detectors, which can provide a better understanding and designing satisfactory devices are also presented. Finally, the challenge and outlook for developing high‐performance lead‐free perovskite X‐ray detectors are also provided.

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.

Background and objectivesThe high transmissibility of SARS-CoV-2 has exposed weaknesses in our infection control and detection measures, particularly in healthcare settings. Aerial sampling has evolved from passive impact filters to active sampling using negative pressure to expose culture substrate for virus detection. We evaluated the effectiveness of an active air sampling device as a potential surveillance system in detecting hospital pathogens, for augmenting containment measures to prevent nosocomial transmission, using SARS-CoV-2 as a surrogate.MethodsWe conducted air sampling in a hospital environment using the AerosolSenseTM air sampling device and compared it with surface swabs for their capacity to detect SARS-CoV-2.ResultsWhen combined with RT-qPCR detection, we found the device provided consistent SARS-CoV-2 detection, compared to surface sampling, in as little as 2 h of sampling time. The device also showed that it can identify minute quantities of SARS-CoV-2 in designated “clean areas” and through a N95 mask, indicating good surveillance capacity and sensitivity of the device in hospital settings.ConclusionActive air sampling was shown to be a sensitive surveillance system in healthcare settings. Findings from this study can also be applied in an organism agnostic manner for surveillance in the hospital, improving our ability to contain and prevent nosocomial outbreaks.

The design of earth-abundant and highly efficient bifunctional electrocatalysts for hydrogen evolution and oxygen evolution reactions (HER/OER) is crucial for hydrogen production through overall water splitting. Herein, we report a novel nanostructure consisting of vertically oriented CoP hierarchical nanosheet arrays with in situ-assembled carbon skeletons on a Ti foil electrode. The novel Zeolitic Imidazolate Framework-67 (ZIF-67) template-derived hierarchical nanosheet architecture effectively improved electrical conductivity, facilitated electrolyte transport, and increased the exposure of the active sites. The obtained bifunctional hybrid exhibited a low overpotential of 72 mV at 10 mA cm−2 and a small Tafel slope of 65 mV dec−1 for HER, and an improved overpotential of 329 mV and a Tafel slope of 107 mV dec−1 for OER. Furthermore, the assembled C@CoP||C@CoP electrolyzer showed excellent overall water splitting performance (1.63 V) at a current density of 10 mA cm−2 and superior durability. This work provides a structure engineering strategy for metal–organic framework (MOF) template-derived hybrids with outstanding electrocatalytic performance.

Chicken manure is one of the popular organic fertilizers used in vegetable farming in Malaysia. Chicken manure is divided into two types, namely broiler chicken manure (BCM) and layer chicken manure (LCM). The effectiveness of these chicken manures is often questionable due to the different method of raising broilers and layers. Therefore, the present study was carried out to determine the effect of the broiler and layer chicken manures on the growth of choy sum (Brassica chinensis L. var. parachinensis), a common farmed leafy vegetable in the country. This study was carried out in the Agricultural Park of Universiti Tunku Abdul Rahman (Perak Campus), Malaysia from February to May 2019. Randomized Complete Block Design (RCBD) methods were used in this study. The chicken manures were composted for roughly 2 months before the experiment. There was no significant difference in the dry weight, plant height and root length of the choy sum treated with either BCM or LCM. Although the choy sum treated with BCM has a higher fresh weight (177.53 g) as compared to that of LCM (134.64 g), this may be due to the natural fluctuation of water content within the plants. Therefore, the results of the present study show that both the chicken manure has a similar effect on the growth of choy sum. The authors recommend further studies on the chemical composition and optimization of chicken manure application in enhancing the growth and yields of leafy vegetables.

Research on the host responses to respiratory viruses could help develop effective interventions and therapies against the current and future pandemics from the host perspective. To explore the pathogenesis that distinguishes SARS-CoV-2 infections from other respiratory viruses, we performed a multi-cohort analysis with integrated bioinformatics and machine learning. We collected 3730 blood samples from both asymptomatic and symptomatic individuals infected with SARS-CoV-2, seasonal human coronavirus (sHCoVs), influenza virus (IFV), respiratory syncytial virus (RSV), or human rhinovirus (HRV) across 15 cohorts. First, we identified an enhanced cellular immune response but limited interferon activities in SARS-CoV-2 infection, especially in asymptomatic cases. Second, we identified a SARS-CoV-2-specific 3-gene signature (CLSPN, RBBP6, CCDC91) that was predominantly expressed by T cells, could distinguish SARS-CoV-2 infection, including Omicron, from other common respiratory viruses regardless of symptoms, and was predictive of SARS-CoV-2 infection before detectable viral RNA on RT-PCR testing in a longitude follow-up study. Thereafter, a user-friendly online tool, based on datasets collected here, was developed for querying a gene of interest across multiple viral infections. Our results not only identify a unique host response to the viral pathogenesis in SARS-CoV-2 but also provide insights into developing effective tools against viral pandemics from the host perspective. [ABSTRACT FROM AUTHOR]

Palm oil production results in many valuable products, but it also generates agricultural wastes such as empty fruit bunch (EFB). EFB composting usually produces nutrient-enriched bio-fertilisers and thus, able to help in reducing the chemical fertilisers applied. Most conventional vegetable farmers in Malaysia solely depend on chemical fertilisers in crop production. However, the intensive use of chemical fertilisers has led to various side effects. Thus, this study was to determine the effect on the growth of choy sum by reducing the dosage of chemical fertiliser with EFB compost as soil amendments. Randomized Complete Block Design (RCBD) methods were used in this study. The fresh weight, dry weight and plant height of the choy sum were found to be not significantly different among all the treatments (T1 – T4) and positive control. This study found that T4 with 30% lesser chemical fertiliser applied showed no significant growth difference with the rest of the treatments indicating that EFB may have the ability to help in reducing chemical fertiliser usage in the growth of choy sum. Further study is recommended as this will help in better EFB waste management and lowering the cost of production for local vegetables.

To survive, animals have to quickly modify their behaviour when the reward changes. The internal representations responsible for this are updated through synaptic weight changes, mediated by certain neuromodulators conveying feedback from the environment. In previous experiments, we discovered a form of hippocampal Spike-Timing-Dependent-Plasticity (STDP) that is sequentially modulated by acetylcholine and dopamine. Acetylcholine facilitates synaptic depression, while dopamine retroactively converts the depression into potentiation. When these experimental findings were implemented as a learning rule in a computational model, our simulations showed that cholinergic-facilitated depression is important for reversal learning. In the present study, we tested the model’s prediction by optogenetically inactivating cholinergic neurons in mice during a hippocampus-dependent spatial learning task with changing rewards. We found that reversal learning, but not initial place learning, was impaired, verifying our computational prediction that acetylcholine-modulated plasticity promotes the unlearning of old reward locations. Further, differences in neuromodulator concentrations in the model captured mouse-by-mouse performance variability in the optogenetic experiments. Our line of work sheds light on how neuromodulators enable the learning of new contingencies. Author summary Reversal learning likely involves changes in synaptic connections, a neural mechanism known as synaptic plasticity, so old information can be updated. We previously discovered that acetylcholine, an important neuromodulator in the brain, changes synaptic connections in a way that favours reversal learning. Specifically, acetylcholine weakens active synapses in brain slices, but these synapses can later be strengthened by a reward signal. Based on this result in slices, we used a computational model to propose a behavioural function for the action of acetylcholine on synaptic connections. In the model, acetylcholine would weaken synaptic connections associated with an old reward, allowing an agent to quickly learn a new reward location. We tested this hypothesis here by silencing acetylcholine neurons in mice while they navigated a maze for food rewards. These animals were able to learn the location of the first food reward, but were impaired when the reward was shifted to a new location. The behavioural results of this study suggest that acetylcholine indeed facilitates reversal learning, which the computational model attributes to a weakening of synaptic connections that do not lead to reward. Taken together, our experimental and computational work show how synaptic strength changes, gated by neuromodulators, affect learning behaviour.

Herring and mackerel are two of the most important pillars of Scottish fisheries. In recent years, global warming has caused a gradual rise in ocean temperatures. In order to survive and reproduce, herring and mackerel populations will migrate. This will have a huge impact on Scotland’s fisheries. Therefore, we need to predict the relocation of fish stocks in advance, make timely adjustments to the fishing range, and minimize the loss of the fishing industry. In this article, we subdivide the research target sea area into 39 regions, establish the optimal SARIMA model for each region based on the collected seawater temperature time series data, and take region 13 and region 15 as examples to fit the ARIMA (3, 3, 1) (1, 2, 1) and ARIMA (2, 3, 1) (0, 2, 1) models with a period of 12. The results show that the SARIMA model fits well in all regions and predicts the temperature changes in the studied sea area from 2021 to 2050. Finally, according to the predicted sea temperature in different periods, the migration position of the fish school is predicted.