Microheterogeneity of Transmission Shapes Submicroscopic Malaria Carriage in Coastal Tanzania.

BACKGROUND: Asymptomatic carriage of malaria parasites persists even as malaria transmission declines. Low-density infections are often submicroscopic, not detected with rapid diagnostic tests (RDTs) or microscopy but detectable by polymerase chain reaction (PCR). METHODS: To characterize submicroscopic Plasmodium falciparum carriage in an area of declining malaria transmission, asymptomatic persons >5 years of age in rural Bagamoyo District, Tanzania, were screened using RDT, microscopy, and PCR. We investigated the size of the submicroscopic reservoir of infection across villages, determined factors associated with submicroscopic carriage, and assessed the natural history of submicroscopic malaria over 4 weeks. RESULTS: Among 6076 participants, P. falciparum prevalences by RDT, microscopy, and PCR were 9%, 9%, and 28%, respectively, with roughly two-thirds of PCR-positive individuals harboring submicroscopic infection. Adult status, female sex, dry season months, screened windows, and bed net use were associated with submicroscopic carriage. Among 15 villages encompassing 80% of participants, the proportion of submicroscopic carriers increased with decreasing village-level malaria prevalence. Over 4 weeks, 23% of submicroscopic carriers (61 of 266) became RDT positive, with half exhibiting symptoms, while half (133 of 266) were no longer parasitemic at the end of 4 weeks. Progression to RDT-positive patent malaria occurred more frequently in villages with higher malaria prevalence. CONCLUSIONS: Microheterogeneity in transmission observed at the village level appears to affect both the size of the submicroscopic reservoir and the likelihood of submicroscopic carriers developing patent malaria in coastal Tanzania.

Inducing Directional Charge Delocalization in 3D-Printable Micro-Supercapacitors Based on Strongly Coupled Black Phosphorus and ReS2 Nanocomposites.

The growing interest in so-called interface coupling strategies arises from their potential to enhance the performance of active electrode materials. Nevertheless, designing a robust coupled interface in nanocomposites for stable electrochemical processes remains a challenge. In this study, an epitaxial growth strategy is proposed by synthesizing sulfide rhenium (ReS2) on exfoliated black phosphorus (E-BP) nanosheets, creating an abundance of robust interfacial linkages. Through spectroscopic analysis using X-ray photoelectron spectroscopy and X-ray absorption spectroscopy, the authors investigate the interfacial environment. The well-developed coupled interface and structural stability contribute to the impressive performance of the 3D-printed E-BP@ReS2-based micro-supercapacitor, achieving a specific capacitance of 47.3 mF cm-2 at 0.1 mA cm-2 and demonstrating excellent long-term cyclability (89.2% over 2000 cycles). Furthermore, density functional theory calculations unveil the positive impact of the strongly coupled interface in the E-BP@ReS2 nanocomposite on the adsorption of H+ ions, showcasing a significantly reduced adsorption energy of -2.17 eV. The strong coupling effect facilitates directional charge delocalization at the interface, enhancing the electrochemical performance of electrodes and resulting in the successful construction of advanced micro-supercapacitors.

End-to-End Network Intrusion Detection Based on Contrastive Learning.

The network intrusion detection system (NIDS) plays a crucial role as a security measure in addressing the increasing number of network threats. The majority of current research relies on feature-ready datasets that heavily depend on feature engineering. Conversely, the increasing complexity of network traffic and the ongoing evolution of attack techniques lead to a diminishing distinction between benign and malicious network behaviors. In this paper, we propose a novel end-to-end intrusion detection framework based on a contrastive learning approach. We design a hierarchical Convolutional Neural Network (CNN) and Gated Recurrent Unit (GRU) model to facilitate the automated extraction of spatiotemporal features from raw traffic data. The integration of contrastive learning amplifies the distinction between benign and malicious network traffic in the representation space. The proposed method exhibits enhanced detection capabilities for unknown attacks in comparison to the approaches trained using the cross-entropy loss function. Experiments are carried out on the public datasets CIC-IDS2017 and CSE-CIC-IDS2018, demonstrating that our method can attain a detection accuracy of 99.9% for known attacks, thus achieving state-of-the-art performance. For unknown attacks, a weighted recall rate of 95% can be achieved.

Research on a Critical Link Discovery Method for Network Security Situational Awareness.

Network security situational awareness (NSSA) aims to capture, understand, and display security elements in large-scale network environments in order to predict security trends in the relevant network environment. With the internet's increasingly large scale, increasingly complex structure, and gradual diversification of components, the traditional single-layer network topology model can no longer meet the needs of network security analysis. Therefore, we conduct research based on a multi-layer network model for network security situational awareness, which is characterized by the three-layer network structure of a physical device network, a business application network, and a user role network. Its network characteristics require new assessment methods, so we propose a multi-layer network link importance assessment metric: the multi-layer-dependent link entropy (MDLE). On the one hand, the MDLE comprehensively evaluates the connectivity importance of links by fitting the link-local betweenness centrality and mapping entropy. On the other hand, it relies on the link-dependent mechanism to better aggregate the link importance contributions in each network layer. The experimental results show that the MDLE has better ordering monotonicity during critical link discovery and a higher destruction efficacy in destruction simulations compared to classical link importance metrics, thus better adapting to the critical link discovery requirements of a multi-layer network topology.

Chromosome-scale genome assembly of medicinal plant Tinospora sagittata (Oliv.) Gagnep. from the Menispermaceae family.

Tinospora sagittata (Oliv.) Gagnep. is an important medicinal tetraploid plant in the Menispermaceae family. Its tuber, Radix Tinosporae, used in traditional Chinese medicine, is rich in diterpenoids and benzylisoquinoline alkaloids (BIAs). To enhance our understanding of medicinal compounds' biosynthesis and Menispermaceae's evolution, we herein report assembling a high-quality chromosome-scale genome with both PacBio HiFi and Illumina sequencing technologies. PacBio Sequel II generated 2.5 million circular consensus sequencing (CCS) reads, and a hybrid assembly strategy with Illumina sequencing resulted in 4483 contigs. The assembled genome size was 2.33 Gb, consisting of 4070 scaffolds (N50 = 42.06 Mb), of which 92.05% were assigned to 26 pseudochromosomes. T. sagittata's chromosomal-scale genome assembly, the first species in Menispermaceae, aids Menispermaceae evolution and T. sagittata's secondary metabolites biosynthesis understanding.

Machine learning models reveal the critical role of nighttime systolic blood pressure in predicting functional outcome for acute ischemic stroke after endovascular thrombectomy.

Background: Blood pressure (BP) is a key factor for the clinical outcomes of acute ischemic stroke (AIS) receiving endovascular thrombectomy (EVT). However, the effect of the circadian pattern of BP on functional outcome is unclear. Methods: This multicenter, retrospective, observational study was conducted from 2016 to 2023 at three hospitals in China (ChiCTR2300077202). A total of 407 patients who underwent endovascular thrombectomy (EVT) and continuous 24-h BP monitoring were included. Two hundred forty-one cases from Beijing Hospital were allocated to the development group, while 166 cases from Peking University Shenzhen Hospital and Hainan General Hospital were used for external validation. Postoperative systolic BP (SBP) included daytime SBP, nighttime SBP, and 24-h average SBP. Least absolute shrinkage and selection operator (LASSO), support vector machine-recursive feature elimination (SVM-RFE), Boruta were used to screen for potential features associated with functional dependence defined as 3-month modified Rankin scale (mRS) score ≥ 3. Nine algorithms were applied for model construction and evaluated using area under the receiver operating characteristic curve (AUC), sensitivity, specificity, and accuracy. Results: Three hundred twenty-eight of 407 (80.6%) patients achieved successful recanalization and 182 patients (44.7%) were functional independent. NIHSS at onset, modified cerebral infarction thrombolysis grade, atrial fibrillation, coronary atherosclerotic heart disease, hypertension were identified as prognostic factors by the intersection of three algorithms to construct the baseline model. Compared to daytime SBP and 24-h SBP models, the AUC of baseline + nighttime SBP showed the highest AUC in all algorithms. The XGboost model performed the best among all the algorithms. ROC results showed an AUC of 0.841 in the development set and an AUC of 0.752 in the validation set for the baseline plus nighttime SBP model, with a brier score of 0.198. Conclusion: This study firstly explored the association between circadian BP patterns with functional outcome for AIS. Nighttime SBP may provide more clinical information regarding the prognosis of patients with AIS after EVT.

Hollow Stair-Stepping Spherical High-Entropy Prussian Blue Analogue for High-Rate Sodium Ion Batteries.

Prussian blue analogues (PBAs) are considered to be one of the most suitable sodium storage materials, especially with the introduction of the high-entropy (HE) concept into their structure to further improve their various abilities. However, severe agglomeration of the HEPBA particles still limits the fast charging capabilities. Here, an HEPBA (Nax(FeMnCoNiCu)[Fe(CN)6]y□1-y·nH2O) with a hollow stair-stepping spherical structure has been prepared through the chemical etching process of the traditional cubic structure of HEPBA. Electrochemical characterization (sodium ion battery), kinetic analysis, and COMSOL Multiphysics simulations reveal that the nature of the high-entropy and the hollow stair-stepping spherical structure can greatly improve the diffusion behavior of Na+ ions. Moreover, the hollow structure effectively mitigates the volume change of HEPBA during SIBs operation, ultimately extending the lifespan. Consequently, the as-prepared HEPBA cathode exhibits excellent rate performance (126.5 and 76.4 mAh g-1 at 0.1 and 4.0 A g-1, respectively) and stable long-term capability (maintaining its 75.6% capacity after 1000 cycles) due to its unique structure. Furthermore, the waste of the etching process can easily be recycled to prepare more HEPBA product. This processing method holds great promise for designing nanostructures of advanced high-entropy Prussian blue analogues for sodium ion batteries.

Ultrathin NiO nanosheets anchored to a nitrogen-doped dodecahedral carbon framework for aqueous potassium-ion hybrid capacitors.

Hierarchical porous structures and well-modulated interfacial interactions are essential for the performance of electrode materials. The energy storage performance can be promoted by regulating the diffusion behavior of the electrolyte and constructing a coupled interaction at heterogeneous interfaces. Herein, we have synthesized ultrathin NiO nanosheets anchored to nitrogen-doped hierarchical porous carbon (NiO/N-HPC) and applied it to construct aqueous potassium ion hybrid capacitors (APIHCs). The abundant and interconnected porous architecture promotes electrolyte penetration/diffusion and shortens the ion transport path, thereby accelerating storage reaction kinetics. The nitrogen-doped carbon support can achieve optimized metal oxides-carbon interaction and enhance the adsorption ability for the electrolyte ions, leading to earning higher storage capacity. Consequently, the prepared NiO/N-HPC exhibits a superior capacitance of 126.4 F g-1 at a current density of 0.5 A g-1, and the as-fabricated NiO/N-HPC//N-HPC APIHC achieves an ultra-high capacitance retention of 91.6% over 8000 cycles at a current density of 2 A g-1. Meanwhile, the APIHC device shows an excellent energy density of 21.95 W h kg-1 and a power density of 9000 W kg-1.