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The shuttle effect of lithium polysulfides (LiPSs) significantly hinders the practical application of lithium-sulfur batteries (LSBs). Herein, a high-entropy hydroxyphosphate (Co_0.29Ni_0.15Fe_0.33Cu_0.16Ca_3.9(PO₄)₃(OH), denoted as HE-CHP), was synthesized by metal cation exchange with calcium hydroxyphosphate (CHP) and then coated on polypropylene (PP) separators to suppress the shuttling of LiPSs. Density functional theory calculations indicated that the various introduced metal cations could effectively modulate the binding strength of soluble polysulfides and enhance the reaction kinetics of LiPSs conversion. As a result, LSBs using the HE-CHP@PP separator exhibited an excellent discharge capacity (1297 mAh g^-1 under 0.2 C) and a slow capacity decay during long-term cycling (0.046 % per cycle at 2 C). At a sulfur loading of up to 6.5 mg cm^-2, the LSB with HE-CHP@PP separator displayed a discharge capacity of 5.8 mAh cm^-2. Notably, the CNT@S||Li Li-S pouch cell with HE-CHP modified separator delivered an initial energy density of 432 Wh kg^-1.

Few-shot Semantic Segmentation (FSS) aims to adapt a pretrained model to new classes with as few as a single labeled training sample per class. Despite the prototype based approaches have achieved substantial success, existing models are limited to the imaging scenarios with considerably distinct objects and not highly complex background, e.g., natural images. This makes such models suboptimal for medical imaging with both conditions invalid. To address this problem, we propose a novel DetailSelf-refinedPrototypeNetwork (DSPNet) to construct high-fidelity prototypes representing the object foreground and the background more comprehensively. Specifically, to construct global semantics while maintaining the captured detail semantics, we learn the foreground prototypes by modeling the multimodal structures with clustering and then fusing each in a channel-wise manner. Considering that the background often has no apparent semantic relation in the spatial dimensions, we integrate channel-specific structural information under sparse channel-aware regulation. Extensive experiments on three challenging medical image benchmarks show the superiority of DSPNet over previous state-of-the-art methods. The code and data are available at https://github.com/tntek/DSPNet.

Molecular diagnosis plays a significant role in detection of biomolecules linked to early stage cancer since it offers greater sensitivity and reliability for identification of biomarker level changes as the disease progresses. The application of vibrational spectroscopy in biomarker detection is defined by the fingerprint spectrum of a molecule originating from single-molecule vibrations. This characteristic makes surface enhanced Raman spectroscopy (SERS) a promising tool for identification of biomarkers. The performance of the SERS technique largely depends on the material being used as the SERS substrate. Graphene, with its large surface area and abundance of aromatic regions, is considered advantageous as SERS substrate. Combining graphene with metal nanomaterials considerably increases SERS signal intensity, thereby enhancing detection sensitivity. Therefore, this review emphasizes the significance of selecting graphene-metal nanohybrids as suitable SERS substrates for signal amplification. The detail understanding of the mechanism of graphene-metal hybrid in SERS based detection of early stage cancer is also presented. Furthermore, several examples demonstrated the application of graphene-metal hybrid nanomaterials in detecting biomarkers and cancer cell differentiation using SERS imaging.

A mouthguard electrochemical sensor for salivary glucose detection based on platinum metal hydrogel is proposed in this work. Conventional enzyme-based electrochemical glucose sensors are fraught with issues such as high cost, oxygen dependency, intricate immobilization procedures, and susceptibility to variations in temperature, pH, and so on. The detection of glucose in saliva, as a non-invasive sensing approach, presents a more convenient solution for diabetes monitoring. This study employs Pt metal hydrogel as the electrocatalytic material for glucose, with its microstructure characterized using scanning electron microscopy (SEM) and X-ray diffraction (XRD) techniques. The sensor's electrochemical properties, sensing performance, anti-interference capability, and stability were assessed through methods including cyclic voltammetry (CV), chronoamperometry, and electrochemical impedance spectroscopy (EIS). Under neutral pH phosphate buffer (PB) solution in the laboratory setting, the sensor demonstrated an outstanding linear range (0-40 mM) and a low detection limit (0.119 mM). Implemented in a wearable mouthguard format, this electrochemical sensor enables the detection of glucose in physiological environments, specifically saliva, exhibiting favorable detection characteristics: a linear range of 0.58-3.08 mM and a detection limit of 0.082 mM. This innovation thus offers a practical and efficacious tool for the non-invasive monitoring of glucose levels relevant to diabetes management.

Completing advanced high school math coursework relates to better adulthood outcomes. Our understanding of why youth with learning disabilities (LDs) and/or ADHD have less access to high math course attainment is limited. Using data on around 20,000 adolescents from the High School Longitudinal Study of 2009, results indicate that, regardless of disability status, structural inequities in family social position are more salient for youth's math course attainment than formal disability programming, universal supports, or structural inequities in how students are sorted across schools. Among youth with the same disability status, youth from higher SES families, or whose parents have a STEM degree, have heightened access to high math course attainment even after accounting for prior achievement. Disparities in access to high math course attainment that persist net of controls for both youth with an LD and youth with ADHD present the possibility of disability-related stratification and stigma during high school.

Vanadium-based oxides have good application prospects in aqueous zinc ion batteries (AZIBs) due to their structures suitable for zinc ion extraction and intercalation. However, their poor conductivity limits their further development. The d-band center plays a key role in promoting adsorption of ions, which promotes the development of electrode materials. Here, a series of MoV₂O₈ compounds with oxygen defect (O_d-MoV₂O₈) were synthesized by a simple hydrothermal process and a subsequent vacuum calcination process through strict control of the deoxidation time. Theoretical calculations reveal that the abundant oxygen vacancies in MoV₂O₈ effectively regulate the d-band center of the zinc ion adsorption site. This precise control of the d-band center enhances the zinc ion adsorption energy of MoV₂O₈, lowers the migration energy barrier for zinc ions, and ultimately significantly boosts zinc storage performance. The specific capacity is as high as 282.4 mAh/g after 100 cycles at 0.1 A/g, and it also shows excellent performance and outstanding cycle life. In addition, the maximum energy density of O_d-MVO-0.5 (MoV₂O₈ sample deoxidized for 0.5 h) is 343.3 Wh kg^-1. Importantly, the mechanism of Zn²⁺ storage in O_d-MoV₂O₈ was revealed by the combination of in situ and ex situ characterization techniques.

Across sub-Saharan Africa, the heavy reliance on mycotoxin-susceptible staple foods means that populations in the region are particularly vulnerable to chronic mycotoxin exposure. This study assessed the exposure risk to ochratoxin A (OTA) and aflatoxins (AFs) from 18 samples of selected staple foods (maize, millet, groundnut) and 56 fresh cow milk samples collected from across Ghana. The foods were sampled simultaneously to maximise comparability, and at two timepoints in March/April (during the dry season) and July/August (during the rainy season) to assess the effects of duration of storage and seasonal conditions on the mycotoxin levels as measured by high-performance liquid chromatography. The margin of exposure (MOE) approach was used to assess the exposure risk from consumption of the sampled foods. Each of the sampled staples was contaminated with OTA (0.19-3.11 ng/g) and at least one AF (0.75-13.05 ng/g B₁, ND-12.12 ng/g B₂, 0.1-9.95 ng/g G₁, ND-16.78 ng/g G₂). Up to 67% had contamination above European Food Safety Authority (EFSA) maximum limits, and 50% were above Ghana Standards Authority (GSA) limits. The fresh cow milk samples were contaminated with AFM1 in the range of 0.05-1.49 ng/g, with 95% above EFSA limits and 36% above GSA limits. Aflatoxin contamination in the staples was high, particularly in July/August when the wet conditions may have adversely impacted the handling and storage of farm produce. Variation in AFM₁ between the two sampling periods mirrored total aflatoxin in the staples, suggesting that even if dairy cattle were grazing in open pasture and not being rationed on stored feed, then there was a high environmental presence of aflatoxigenic fungi. The MOE estimates were ≤ 533.09, far below the safe cut-off of 10,000 for suspected carcinogenic compounds. The high mycotoxin levels indicate a priority risk to child nutrition which relies heavily on cereal mixes based on one or all the three sampled staples. The data from this study underscore the urgent need for interventions to better appreciate and address mycotoxin exposure for enhanced food security and public health in Ghana and across sub-Saharan Africa.

Worldwide attention is focused on microplastics environmental pollution, primarily for its potential negative effects on biota and human health. It is of great importance to identify standardized analytical methods to have an objective feedback about this concern. The recent regulation regarding the intentionally added microplastics content and the attention for the unintentional microplastics release are the basis of this work, whose topic is the development of an analytical method for microbeads (spheres) and microparticles (fragments) determination in certain cosmetic samples, in particular creamy samples. The method is based on Accelerated Solvent Extraction technique to remove all the sample matrix ingredients. The final suspension was then filtered on silicon membrane, for the following quali-quantitative micro-FTIR analysis, and on glass fibre membranes, for the gravimetric analysis. The method was developed for a theoretical microplastics concentration of 0.025 % (w/w) and allows a good recovery percentage. Working both by gravimetric evaluation and by micro-FTIR analysis gives more confident results and guaranties a proper identification and characterization of the filtered materials.

Considering the close association between cardiac troponin I (cTnI) level and various cardiovascular diseases, it becomes essential to explore sensitive and accurate detection methods for monitoring their levels in the early stages of disease. In this work, a magnetic dual-aptamer electrochemical sensor for cTnI detection was constructed in the first utilizing MOF-on-MOF-derived electrocatalyst as a signal amplifier in collaboration with high-efficient separation of magnetic beads (MBs). Employing zeolitic imidazolate framework-67 (ZIF-67) with high surface area as host MOF, MOF-on-MOF heterostructure (ZIF-67@PBA) was facilely prepared by in-situ growth of conductive prussian blue analogue (PBA) as guest MOF onto the surface of ZIF-67 with a simple ion-exchange method. After low-temperature calcination, N doped derived electrocatalyst (N-ZIF-67@PBA) was obtained with intact skeletons and pore structures of MOFs. This not only integrated bimetallic active centers with various valence states and diversiform nanostructures of dual MOF, but endowed N-ZIF-67@PBA 8.3-fold increase of electrocatalytic activity for catalytic amplification. Further using aptamer-modified MBs as capture carriers for recognizing and separating cTnI from complex samples with high specificity, the magnetic dual-aptamer sensor successfully achieved the sensitive detection of cTnI with a low detection limit of 0.31 fg/mL. This work provided a new viewpoint on the use of MOF-on-MOF-derived electrocatalyst for ultrasensitive electrochemical sensing analysis.

Exosomes, emerging as ideal non-invasive biomarkers for disease diagnosis and monitoring, have seldom been explored based on metabolite levels. In this study, we designed and synthesized a pH-responsive phase-transition bifunctional affinity nanopolymer (pH-BiAN) that could efficiently and homogeneously separate exosomes from urine. Specifically, poly-4-vinylpyridine (P4VP) was chosen as the pH-responsive polymer and simultaneously modified with two exosome-affinity components CD63 aptamer and distearoyl phosphoethanolamine (DSPE) through a one-step amide reaction at room temperature. By utilizing two distinct but synergistic affinity mechanisms-the immune affinity between CD63 aptamer and exosomal CD63 proteins, and hydrophobic interactions between the DSPE and the exosomal lipids-pH-BiAN can enable efficient and specific exosome separation. Moreover, during the urine exosome capture procedure, the pH-BiAN outperforms conventional solid exosome separation materials by remaining soluble in the urine sample, significantly enhancing mass transfer and contact efficiency. After exosome capture, pH-BiAN can quickly aggregate and convert to solid upon pH adjustment, allowing for easy centrifugation separation. Afterwards, multiple machine learning models were established by combining liquid chromatography-mass spectrometry/mass spectrometry (LC-MS/MS) untargeted metabolomics for isolated exosomes, and the clinical accuracy of the training and test sets was more than 0.919, which could well distinguish early osteoarthritis patients from healthy people.