This review portrays a comparison between green protocols and conventional nanoparticle (NP) synthesis strategies, highlighting each method\'s advantages and limitations. Various top-down and bottom-up methods in NP synthesis are described in detail. The green chemistry principles are emphasized for designing safe processes for nanomaterial synthesis. Among the green biogenic sources plant extracts, vitamins, enzymes, polysaccharides, fungi (Molds and mushrooms), bacteria, yeast, algae, and lichens are discussed. Limitations in the reproducibility of green protocols in terms of availability of raw material, variation in synthetic protocol, and selection of material due to geographical differences are elaborated. Finally, a conclusion is drawn utilizing green chemical principles, & a circular economy strategy to minimize waste generation, offering a promising framework for the synthesis of NPs emphasizing sustainability.

Established in recent years as an important approach to unraveling the heterogeneity of intact monoclonal antibodies, native mass spectrometry has been rarely utilized for sequencing these complex biomolecules via tandem mass spectrometry. Typically, top-down mass spectrometry has been performed starting from highly charged precursor ions obtained via electrospray ionization under denaturing conditions (i.e., in the presence of organic solvents and acidic pH). Here we systematically benchmark four distinct ion dissociation methods─namely, higher-energy collisional dissociation, electron transfer dissociation, electron transfer dissociation/higher-energy collisional dissociation, and 213 nm ultraviolet photodissociation─in their capability to characterize a therapeutic monoclonal antibody, trastuzumab, starting from denatured and native-like precursor ions. Interestingly, native top-down mass spectrometry results in higher sequence coverage than the experiments carried out under denaturing conditions, with the exception of ultraviolet photodissociation. Globally, electron transfer dissociation followed by collision-based activation of product ions generates the largest number of backbone cleavages in disulfide protected regions, including the complementarity determining regions, regardless of electrospray ionization conditions. Overall, these findings suggest that native mass spectrometry can certainly be used for the gas-phase sequencing of whole monoclonal antibodies, although the dissociation of denatured precursor ions still returns a few backbone cleavages not identified in native experiments. Finally, a comparison of the fragmentation maps obtained under denaturing and native conditions strongly points toward disulfide bonds as the primary reason behind the largely overlapping dissociation patterns.

The kinetic demands of the spine can be assessed using a top-down (TD) or bottom-up (BU) approach, which start calculations from the either the hands or from the feet, respectively. Biomechanists have traditionally favored a BU approach, though existing modeling approaches encourage a TD approach. Regardless of the approach the demands should be similar, provided the external forces and linked segment parameters are equivalently measured and modeled. Demonstrating a level of agreement between the two approaches can help evaluate a model. Further, having both approaches can be advantageous when data is inaccurate or unavailable for one. The purpose of this study was to compare the internal moments and forces at multiple lumbar and thoracic intervertebral joint (IVJ) levels during lifting tasks from an established OpenSim thoracolumbar spine model that applies a TD approach and a similar model modified to adopt a BU approach. Kinematics and external forces were recorded from twelve participants during sagittal and lateral lifts of different lifting speeds and crate masses. For both approaches IVJ kinetics were estimated using a standard OpenSim modeling pipeline. The BU and TD approach IVJ joint moments generally agreed both temporally (R2 = .94 ± .17) and in magnitude (RMSE=6.2 ± 3.5 Nm) of the primary planes of movement. There were however some temporal fit exceptions for off axes moments with low magnitudes (i.e., < 10 Nm). Bland-Altman plots also indicated acceptable agreement for IVJ peak forces (BU-TD difference of 12 ± 111 and 8 ± 31 N in compression and resultant shear, respectfully). These results support the application of the BU approach and the assigned linked segment parameters of the model. The new BU model is available on the SimTK site (https://simtk.org/projects/spine_ribcage).

[This corrects the article DOI: 10.3389/fnana.2019.00022.].

Nitrogen trifluoride (NF3) is a potent and long-lived greenhouse gas that is widely used in the manufacture of semiconductors, photovoltaic cells, and flat panel displays. Using atmospheric observations from eight monitoring stations from the Advanced Global Atmospheric Gases Experiment (AGAGE) and inverse modeling with a global 3-D atmospheric chemical transport model (GEOS-Chem), we quantify global and regional NF3 emission from 2015 to 2021. We find that global emissions have grown from 1.93 ± 0.58 Gg yr-1 (± one standard deviation) in 2015 to 3.38 ± 0.61 Gg yr-1 in 2021, with an average annual increase of 10% yr-1. The available observations allow us to attribute significant emissions to China (0.93 ± 0.15 Gg yr-1 in 2015 and 1.53 ± 0.20 Gg yr-1 in 2021) and South Korea (0.38 ± 0.07 Gg yr-1 to 0.65 ± 0.10 Gg yr-1). East Asia contributes around 73% of the global NF3 emission increase from 2015 to 2021: approximately 41% of the increase is from emissions from China (with Taiwan included), 19% from South Korea, and 13% from Japan. For Japan, which is the only one of these three countries to submit annual NF3 emissions to UNFCCC, our bottom-up and top-down estimates are higher than reported. With increasing demand for electronics, especially flat panel displays, emissions are expected to further increase in the future.

Sensory perception is dynamic, quickly adapting to sudden shifts in environmental or behavioral context. Although decades of work have established that these dynamics are mediated by rapid fluctuations in sensory cortical activity, we have a limited understanding of the brain regions and pathways that orchestrate these changes. Neurons in the orbitofrontal cortex (OFC) encode contextual information, and recent data suggest that some of these signals are transmitted to sensory cortices. Whether and how these signals shape sensory encoding and perceptual sensitivity remain uncertain. Here, we asked whether the OFC mediates context-dependent changes in auditory cortical sensitivity and sound perception by monitoring and manipulating OFC activity in freely moving Mongolian gerbils of both sexes under two behavioral contexts: passive sound exposure and engagement in an amplitude modulation (AM) detection task. We found that the majority of OFC neurons, including the specific subset that innervates the auditory cortex, were strongly modulated by task engagement. Pharmacological inactivation of the OFC prevented rapid context-dependent changes in auditory cortical firing and significantly impaired behavioral AM detection. Our findings suggest that contextual information from the OFC mediates rapid plasticity in the auditory cortex and facilitates the perception of behaviorally relevant sounds.

BACKGROUND: Various neurocognitive models explore perceptual distortions and hallucinations in schizophrenia and the general population. A variant of predictive coding account suggests that strong priors, like cognitive expectancy, may influence perception. This study examines if stronger cognitive expectancies result in more auditory false percepts in clinical and healthy control groups, investigates group differences, and explores the association between false percepts and hallucinations.
METHODS: Patients diagnosed with schizophrenia with current auditory hallucinations (n = 51) and without hallucinations (n = 66) and healthy controls (n = 51) underwent the False Perception Task under various expectancy conditions. All groups were examined for the presence and severity of hallucinations or hallucinatory-like experiences.
RESULTS: We observed a main effect of condition across all groups, ie, the stronger the cognitive expectancy, the greater the ratio of auditory false percepts. However, there was no group effect for the ratio of auditory false percepts. Despite modest pairwise correlations in the hallucinating group, the ratio of auditory false percepts was not predicted by levels of hallucinations and hallucinatory-like experiences in a linear mixed model.
CONCLUSIONS: The current study demonstrates that strong priors in the form of cognitive expectancies affect perception and play a role in perceptual disturbances. There is also a tentative possibility that overreliance on strong priors may be associated with hallucinations in currently hallucinating subjects. Possible, avoidable confounding factors are discussed in detail.

Combining the physical advantages of two-dimensional (2D) inorganic nanosheets and the modular design and programmed structure of metal-organic frameworks (MOFs), 2D MOFs remain at the forefront of functional material research. Despite tremendous efforts, precise control in the synthesis of 2D nonlayered MOFs with predesigned topology for desired applications remains challenging. Success in the bottom-up synthesis of 2D nonlayered MOFs via ligand exchange motivated us to incorporate partial BTC (BTC = 1,3,5-benzenetricarboxylate) ligand dissociation and CO2 capped coordination into the top-down treatment of bulk Cu-BTC MOF, leading to successful conversion of a 3D nonlayered network to a 2D Cu-based topological structure. Notably, a supercritical CO2-containing solvent mixture is employed to provide the desired defect and coordination engineering. Thus, our work introduces a new top-down concept based on modulated synthesis to fabricate high-quality 2D nonlayered MOFs for the first time.

Poultry managers can better understand the state of poultry through poultry behavior analysis. As one of the key steps in behavior analysis, the accurate estimation of poultry posture is the focus of this research. This study mainly analyzes a top-down pose estimation method of multiple chickens. Therefore, we propose the \"multi-chicken pose\" (MCP), a pose estimation system for multiple chickens through deep learning. Firstly, we find the position of each chicken from the image via the chicken detector; then, an estimate of the pose of each chicken is made using a pose estimation network, which is based on transfer learning. On this basis, the pixel error (PE), root mean square error (RMSE), and image quantity distribution of key points are analyzed according to the improved chicken keypoint similarity (CKS). The experimental results show that the algorithm scores in different evaluation metrics are a mean average precision (mAP) of 0.652, a mean average recall (mAR) of 0.742, a percentage of correct keypoints (PCKs) of 0.789, and an RMSE of 17.30 pixels. To the best of our knowledge, this is the first time that transfer learning has been used for the pose estimation of multiple chickens as objects. The method can provide a new path for future poultry behavior analysis.

Antibodies are one of the most formidable molecular weapons available to our immune system. Their high specificity against a target (antigen) and capability of triggering different immune responses (e.g., complement system activation and antibody-dependent cell-mediated cytotoxicity) make them ideal drugs to fight many different human diseases. Currently, both monoclonal antibodies and more complex molecules based on the antibody scaffold are used as biologics. Naturally, such highly heterogeneous molecules require dedicated analytical methodologies for their accurate characterization. Mass spectrometry (MS) can define the presence and relative abundance of multiple features of antibodies, including critical quality attributes. The combination of small and large variations within a single molecule can only be determined by analyzing intact antibodies or their large (25 to 100 kDa) subunits. Hence, top-down (TD) and middle-down (MD) MS approaches have gained popularity over the last decade. In this Young Scientist Feature we discuss the evolution of TD and MD MS analysis of antibodies, including the new frontiers that go beyond biopharma applications. We will show how this field is now moving from the \"quality control\" analysis of a known, single antibody to the high-throughput investigation of complex antibody repertoires isolated from clinical samples, where the ultimate goal is represented by the complete gas-phase sequencing of antibody molecules without the need of any a priori knowledge.