Mushroom poisoning of Panaeolus subbalteatus from Ningxia, northwest China, with species identification and tryptamine detection.

Mushroom poisoning is a significant contributor to foodborne disease outbreaks in China. This study focuses on two Panaeolus subbalteatus poisoning incidents accompanied by epidemiological investigations, species identification, and toxin detection in Ningxia, northwest China. In these two poisoning incidents, some patients exhibited gastrointestinal or neurological symptoms approximately 0.5 h after ingestion of a large amount of wild mushroom. Specifically, in Case 1, one of the three patients experienced nausea, vomiting, and numbness in the throat and limbs; in Case 2, one patient reported dizziness and an abnormal sense of direction. Through morphological and phylogenetic analyses, mushroom specimens were identified as P. subbalteatus. Psilocybin and psilocin were detected in mushroom samples, and only psilocin was detected in biological samples by liquid chromatography-triple quadrupole-linear ion trap mass spectrometry screening. The average psilocybin and psilocin contents in mushroom samples were 1532.2-1760.7 and 114.5-136.0 mg/kg (n = 3), respectively. Moreover, only psilocin was detected in blood and urine samples, with average concentrations 0.5-1.2 ng/mL (n = 3) and 2.5-3.1 ng/mL (n = 3), respectively. These findings provide technical support for managing similar incidents in the future.

Common functional mechanisms underlying dynamic brain network changes across five general anesthetics: A rat fMRI study.

BACKGROUND: Reversible loss of consciousness is the primary therapeutic endpoint of general anesthesia; however, the drug-invariant mechanisms underlying anesthetic-induced unconsciousness are still unclear. This study aimed to investigate the static, dynamic, topological and organizational changes in functional brain network induced by five clinically-used general anesthetics in the rat brain. METHOD: Male Sprague-Dawley rats (n = 57) were randomly allocated to received propofol, isoflurane, ketamine, dexmedetomidine, or combined isoflurane plus dexmedetomidine anesthesia. Resting-state functional magnetic resonance images were acquired under general anesthesia and analyzed for changes in dynamic functional brain networks compared to the awake state. RESULTS: Different general anesthetics induced distinct patterns of functional connectivity inhibition within brain-wide networks, resulting in multi-level network reorganization primarily by impairing the functional connectivity of cortico-subcortical networks as well as by reducing information transmission capacity, intrinsic connectivity, and network architecture stability of subcortical regions. Conversely, functional connectivity and topological properties were preserved within cortico-cortical networks, albeit with fewer dynamic fluctuations under general anesthesia. CONCLUSIONS: Our findings highlighted the effects of different general anesthetics on functional brain network reorganization, which might shed light on the drug-invariant mechanism of anesthetic-induced unconsciousness.

Two Photosensitive Dermatitis Outbreaks Caused by Cordierites frondosus - Chuxiong Yi Autonomous Prefecture, Yunnan Province, China, 2023.

What is already known about this topic?: Cordierites frondosus (C. frondosus) is a species of toxic mushroom known to induce symptoms of photosensitive dermatitis. What is added by this report?: In the months of May and June 2023, a total of four patients in Chuxiong Yi Autonomous Prefecture, Yunnan Province, were affected by C. frondosus poisoning, occurring over two distinct incidents. The condition of two patients deteriorated after they were re-exposed to sunlight on the seventh day following the initial poisoning. Separately, an additional two patients reported experiencing a mild, needle-like sensation on areas of their skin exposed to the sun, recorded on the twelfth day subsequent to the poisoning. What are the implications for public health practice?: Given that symptoms of photosensitive dermatitis, a potential severe consequence of C. frondosus poisoning, can manifest up to a week post-sun exposure, it is advisable to avoid sunlight for a minimum of two weeks following poisoning.

Genomic context- and H2AK119 ubiquitination-dependent inheritance of human Polycomb silencing.

Polycomb repressive complexes 1 and 2 (PRC1 and 2) are required for heritable repression of developmental genes. The cis- and trans-acting factors that contribute to epigenetic inheritance of mammalian Polycomb repression are not fully understood. Here, we show that, in human cells, ectopically induced Polycomb silencing at initially active developmental genes, but not near ubiquitously expressed housekeeping genes, is inherited for many cell divisions. Unexpectedly, silencing is heritable in cells with mutations in the H3K27me3 binding pocket of the Embryonic Ectoderm Development (EED) subunit of PRC2, which are known to disrupt H3K27me3 recognition and lead to loss of H3K27me3. This mode of inheritance is less stable and requires intact PRC2 and recognition of H2AK119ub1 by PRC1. Our findings suggest that maintenance of Polycomb silencing is sensitive to local genomic context and can be mediated by PRC1-dependent H2AK119ub1 and PRC2 independently of H3K27me3 recognition.

Enantioselective α-Trifluoromethylthiolation of Carbonyl Compounds with AgSCF3 and Trichloroisocyanuric Acid.

We successfully developed an enantioselective trifluoromethylthiolation of structurally diverse carbonyl compounds. Trichloroisocyanuric acid and AgSCF3 were employed to generate active electrophilic trifluoromethylthio species in situ for asymmetric C-SCF3 bond formation. A broad variety of chiral SCF3-carbon nucleophiles (pyrazolones, ß-keto esters, and ß-keto amides) were obtained in excellent yields with high enantioselectivities (up to 92% ee) by Cinchona alkaloid derived squaramide catalysts. The reaction exhibits high efficiency, good enantioselectivity, and high functional group tolerance, which provided a novel and efficient way for asymmetric synthesis of trifluoromethylthiolated carbonyl compounds.

Simple Behavioral Analysis (SimBA) as a platform for explainable machine learning in behavioral neuroscience.

The study of complex behaviors is often challenging when using manual annotation due to the absence of quantifiable behavioral definitions and the subjective nature of behavioral annotation. Integration of supervised machine learning approaches mitigates some of these issues through the inclusion of accessible and explainable model interpretation. To decrease barriers to access, and with an emphasis on accessible model explainability, we developed the open-source Simple Behavioral Analysis (SimBA) platform for behavioral neuroscientists. SimBA introduces several machine learning interpretability tools, including SHapley Additive exPlanation (SHAP) scores, that aid in creating explainable and transparent behavioral classifiers. Here we show how the addition of explainability metrics allows for quantifiable comparisons of aggressive social behavior across research groups and species, reconceptualizing behavior as a sharable reagent and providing an open-source framework. We provide an open-source, graphical user interface (GUI)-driven, well-documented package to facilitate the movement toward improved automation and sharing of behavioral classification tools across laboratories.

High-throughput direct screening of restriction endonuclease using a microfluidic fluorescence-activated drop sorter based on the SOS response in Escherichia coli.

A restriction endonuclease (RE) is an enzyme that can recognize a specific DNA sequence and cleave that DNA into fragments with double-stranded breaks. This sequence-specific cleaving ability and its ease of use have made REs commonly used tools in molecular biology since their first isolation and characterization in 1970s. While artificial REs still face many challenges in large-scale synthesis and precise activity control for practical use, searching for new REs in natural samples remains a viable route to expanding the RE pool for fundamental research and industrial applications. In this paper, we propose a new strategy to search for REs in an efficient manner. We constructed a host bacterial cell to link the genotype of REs to the phenotype of ß-galactosidase expression based on the bacterial SOS response, and used a high-throughput microfluidic platform to isolate, detect and sort the REs in microfluidic drops at a frequency of ∼800 drops per second. We employed this strategy to screen for the XbaI gene from the constructed libraries of varied sizes. In a single round of sorting, a 90-fold target enrichment was achieved within 1 h. Compared to conventional RE-screening methods, the direct screening approach that we propose excels at efficient search of desirable REs in natural samples - especially unculturable samples - and can be tailored to high-throughput screening of a wide range of genotoxic targets.

3D SHINKEI MR neurography in evaluation of traumatic brachial plexus.

3D SHINKEI neurography is a new sequence for imaging the peripheral nerves. The study aims at assessing traumatic brachial plexus injury using this sequence. Fifty-eight patients with suspected trauma induced brachial plexus injury underwent MR neurography (MRN) imaging in 3D SHINKEI sequence at 3 T. Surgery and intraoperative somatosensory evoked potentials or clinical follow-up results were used as the reference standard. MRN, surgery and electromyography (EMG) findings were recorded at four levels of the brachial plexus-roots, trunks, cords and branches. Fifty-eight patients had pre- or postganglionic injury. The C5-C6 nerve postganglionic segment was the most common (average 42%) among the postganglionic injuries detected by 3D SHINKEI MRN. The diagnostic accuracy (83.75%) and the specificity (90.30%) of MRN higher than that of EMG (p < 0.001). There was no significant difference in the diagnostic sensitivity of MRN compared with EMG (p > 0.05). Eighteen patients with brachial plexus injury underwent surgical exploration after MRN examination and the correlation between MRN and surgery was 66.7%. Due to the high diagnostic accuracy and specificity, 3D SHINKEI MRN can comprehensively display the traumatic brachial plexus injury. This sequence has great potential in the accurate diagnosis of traumatic brachial plexus injury.

Construction of an Angular Tricyclic Benzofuran Skeleton Using the C-H Activation Strategy.

A protocol for the construction of an angular tricyclic benzofuran skeleton based on the C-H activation strategy has been established. Different phthalide lactones on this skeleton can be easily assembled with various side chains by using C-H activation with aldehydes and subsequent reduction. This skeleton provides a versatile and crucial motif for the total synthesis of naturally occurring angular tricyclic benzofurans and their derivatives. Based on this protocol, the improved total syntheses of daldinin A and annullatin D were achieved in yields of 17.3 and 7.6%, respectively.

Mushroom Poisoning Outbreaks - China, 2023.

What is already known about this topic?: Mushroom poisoning poses a significant food safety concern in China, with a total of 196 species identified in poisoning incidents by the end of 2022. What is added by this report?: In 2023, the China CDC conducted an investigation into 505 cases of mushroom poisoning spanning 24 provincial-level administrative divisions. This investigation resulted in 1,303 patients and 16 deaths, yielding a case fatality rate of 1.23%. A total of 97 mushrooms were identified as the cause of 6 distinct clinical disease types, with 12 species newly documented as poisonous mushrooms in China. What are the implications for public health practice?: Close collaboration among CDC staff, physicians, and mycologists remains crucial for the control and prevention of mushroom poisoning in the future.

Investigation of acousto-optic interaction with momentum mismatching considering acoustic anisotropy in birefringent crystal.

In this work, the momentum mismatching based on which the acousto-optic (AO) transfer function and diffraction efficiency was acquired, was calculated considering the properties of AO crystals in AO interactions in acousto-optic tunable filter (AOTF). Transfer functions were obtained using a 4f optical system combined with AOTF and compared with theoretical calculations. It demonstrated the influence of acoustic energy shift on the AO interaction which should be considered in the design of AOTF.

Individual Differences in Volitional Social Self-Administration and Motivation in Male and Female Mice Following Social Stress.

BACKGROUND: A key challenge in developing treatments for neuropsychiatric illness is the disconnect between preclinical models and the complexity of human social behavior. We integrate voluntary social self-administration into a rodent model of social stress as a platform for the identification of fundamental brain and behavior mechanisms underlying stress-induced individual differences in social motivation. METHODS: Here, we introduced an operant social stress procedure in male and female mice composed of 3 phases: 1) social self-administration training, 2) social stress exposure concurrent with reinforced self-administration testing, and 3) poststress operant testing under nonreinforced and reinforced conditions. We used social-defeat and witness-defeat stress in male and female mice. RESULTS: Social defeat attenuated social reward seeking in males but not females, whereas witness defeat had no effect in males but promoted seeking behavior in females. We resolved social stress-induced changes to social motivation by aggregating z-scored operant metrics into a cumulative social index score to describe the spectrum of individual differences exhibited during operant social stress. Clustering does not adequately describe the relative distributions of social motivation following stress and is better described as a nonbinary behavioral distribution defined by the social index score, capturing a dynamic range of stress-related alterations in social motivation inclusive of sex as a biological variable. CONCLUSIONS: We demonstrated that operant social stress can detect stable individual differences in stress-induced changes to social motivation. The inclusion of volitional behavior in social procedures may enhance the understanding of behavioral adaptations that promote stress resiliency and their mechanisms under more naturalistic conditions.

Perovskite Oxide as A New Platform for Efficient Electrocatalytic Nitrogen Oxidation.

Electrocatalytic nitrogen oxidation reaction (NOR) offers an efficient and sustainable approach for conversion of widespread nitrogen (N2 ) into high-value-added nitrate (NO3 - ) under mild conditions, representing a promising alternative to the traditional approach that involves harsh Haber-Bosch and Ostwald oxidation processes. Unfortunately, due to the weak absorption/activation of N2 and the competitive oxygen evolution reaction, the kinetics of NOR process is extremely sluggish accompanied with low Faradaic efficiencies and NO3 - yield rates. In this work, an oxygen-vacancy-enriched perovskite oxide with nonstoichiometric ratio of strontium and ruthenium (denoted as Sr0.9 RuO3 ) was synthesized and explored as NOR electrocatalyst, which can exhibit a high Faradaic efficiency (38.6 %) with a high NO3 - yield rate (17.9 µmol mg-1 h-1 ). The experimental results show that the amount of oxygen vacancies in Sr0.9 RuO3 is greatly higher than that of SrRuO3 , following the same trend as their NOR performance. Theoretical simulations unravel that the presence of oxygen vacancies in the Sr0.9 RuO3 can render a decreased thermodynamic barrier toward the oxidation of *N2 to *N2 OH at the rate-determining step, leading to its enhanced NOR performance.

Unsupervised Fusion of Misaligned PAT and MRI Images via Mutually Reinforcing Cross-Modality Image Generation and Registration.

Photoacoustic tomography (PAT) and magnetic resonance imaging (MRI) are two advanced imaging techniques widely used in pre-clinical research. PAT has high optical contrast and deep imaging range but poor soft tissue contrast, whereas MRI provides excellent soft tissue information but poor temporal resolution. Despite recent advances in medical image fusion with pre-aligned multimodal data, PAT-MRI image fusion remains challenging due to misaligned images and spatial distortion. To address these issues, we propose an unsupervised multi-stage deep learning framework called PAMRFuse for misaligned PAT and MRI image fusion. PAMRFuse comprises a multimodal to unimodal registration network to accurately align the input PAT-MRI image pairs and a self-attentive fusion network that selects information-rich features for fusion. We employ an end-to-end mutually reinforcing mode in our registration network, which enables joint optimization of cross-modality image generation and registration. To the best of our knowledge, this is the first attempt at information fusion for misaligned PAT and MRI. Qualitative and quantitative experimental results show the excellent performance of our method in fusing PAT-MRI images of small animals captured from commercial imaging systems.

TestFit: A plug-and-play one-pass test time method for medical image segmentation.

Deep learning (DL) based methods have been extensively studied for medical image segmentation, mostly emphasizing the design and training of DL networks. Only few attempts were made on developing methods for applying DL models in test time. In this paper, we study whether a given off-the-shelf segmentation network can be stably improved on-the-fly during test time in an online processing-and-learning fashion. We propose a new online test-time method, called TestFit, to improve results of a given off-the-shelf DL segmentation model in test time by actively fitting the test data distribution. TestFit first creates a supplementary network (SuppNet) from the given trained off-the-shelf segmentation network (this original network is referred to as OGNet) and applies SuppNet together with OGNet for test time inference. OGNet keeps its hypothesis derived from the original training set to prevent the model from collapsing, while SuppNet seeks to fit the test data distribution. Segmentation results and supervision signals (for updating SuppNet) are generated by combining the outputs of OGNet and SuppNet on the fly. TestFit needs only one pass on each test sample - the same as the traditional test model pipeline - and requires no training time preparation. Since it is challenging to look at only one test sample and no manual annotation for model update each time, we develop a series of technical treatments for improving the stability and effectiveness of our proposed online test-time training method. TestFit works in a plug-and-play fashion, requires minimal hyper-parameter tuning, and is easy to use in practice. Experiments on a large collection of 2D and 3D datasets demonstrate the capability of our TestFit method.

An arginine-rich nuclear localization signal (ArgiNLS) strategy for streamlined image segmentation of single-cells.

High-throughput volumetric fluorescent microscopy pipelines can spatially integrate whole-brain structure and function at the foundational level of single-cells. However, conventional fluorescent protein (FP) modifications used to discriminate single-cells possess limited efficacy or are detrimental to cellular health. Here, we introduce a synthetic and non-deleterious nuclear localization signal (NLS) tag strategy, called 'Arginine-rich NLS' (ArgiNLS), that optimizes genetic labeling and downstream image segmentation of single-cells by restricting FP localization near-exclusively in the nucleus through a poly-arginine mechanism. A single N-terminal ArgiNLS tag provides modular nuclear restriction consistently across spectrally separate FP variants. ArgiNLS performance in vivo displays functional conservation across major cortical cell classes, and in response to both local and systemic brain wide AAV administration. Crucially, the high signal-to-noise ratio afforded by ArgiNLS enhances ML-automated segmentation of single-cells due to rapid classifier training and enrichment of labeled cell detection within 2D brain sections or 3D volumetric whole-brain image datasets, derived from both staining-amplified and native signal. This genetic strategy provides a simple and flexible basis for precise image segmentation of genetically labeled single-cells at scale and paired with behavioral procedures.

The maca protein ameliorates DSS-induced colitis in mice by modulating the gut microbiota and production of SCFAs.

Maca is a functional food with anti-inflammatory activity, and it is rich in protein. Currently, inflammatory bowel disease (IBD) is a common gastrointestinal disease. However, there is little research focusing on the effect of maca protein (MCP) on IBD. In this study, we extracted MCP from maca root and explored its effect and mechanism on improving dextran sodium sulfate (DSS)-induced IBD in mice. The results indicated that MCP intervention alleviated the clinical symptoms and colon tissue damage of mice with DSS-induced colitis and inhibited the expression of inflammatory factors. Moreover, it can modulate the gut microbiota composition in mice with DSS-induced colitis. The regulation is achieved by reducing the relative abundance of the IBD-exacerbating key bacterial genera: Lachnospiraceae_NK4A136_group, Bacteroides, Desulfovibrio, Prevotella, Helicobacter and Sutterella, while increasing the relative abundance of the IBD-alleviating key bacterial genera: norank_f_Muribaculaceae, Lactobacillus, Oscillospira, Akkermansia and Bifidobacterium. MCP can also promote the production of short-chain fatty acids (SCFAs). The further western blotting results indicated that MCP can regulate the Treg/Th17 immune balance in mice with colitis via the SCFAs-GPR41/43/HDAC1 signaling pathway. Overall, MCP can alleviate colitis by comprehensively regulating the gut microbiota and inflammatory response. It may be a promising functional component that reduces the risk of colitis by maintaining intestinal health.

Contact-Inhibited ERK Signaling is Determined by Cellular-Resolution Western Blotting.

Extracellular signal-regulated kinase (ERK) signaling is essential to regulated cell behaviors, including cell proliferation, differentiation, and apoptosis. The influence of cell-cell contacts on ERK signaling is central to epithelial cells, yet few studies have sought to understand the same in cancer cells, particularly with single-cell resolution. To acquire both phenotypic (cell-contact state) and proteomic profile (ERK phosphorylation) on the same HeLa cells, we prepend high-content, whole-cell imaging prior to endpoint cellular-resolution western blot analyses for hundreds of cancer cells cultured on chip. By indexing the phosphorylation level of ERK in each cell or cell-contact cluster to the imaged cell-contact state, we compare ERK signaling between isolated and in-contact cells. We observe attenuated (∼2×) ERK signaling in HeLa cells which are in contact versus isolated. Attenuation is sustained when the HeLa cells are challenged with hyperosmotic stress. The contact-dependent differential ERK-phosphorylation corresponds to the differential EGFR distribution on cell surfaces, suggesting the involvement of EGFRs in contact-inhibited ERK signaling. Our findings show the impact of cell-cell contacts on ERK activation with isolated and in-contact cells, hence providing a new tool into control and scrutiny of cell-cell interactions.

Neuralgic amyotrophy: sensitivity and specificity of magnetic resonance neurography in diagnosis: A retrospective study.

BACKGROUND: Neuralgic amyotrophy (NA) is a clinically acute or subacute disease. To study the characteristics of brachial plexus magnetic resonance neurography (MRN) in patients with NA, and to explore the clinical application value of MRN combined with electromyography (EMG) in the diagnosis of NA. METHODS: Brachial plexus MRN images of 32 patients with NA were retrospectively analyzed, and their characteristics were investigated. The accuracy, sensitivity and specificity of MRN, EMG, and the combination of the 2 methods for NA diagnosis were compared. RESULTS: Among the 32 patients with NA, 28 (87.5%) cases of unilateral brachial plexus involvement, 18 (56.3%) cases of multiple nerve roots involvement. In 10 cases, C5 nerve roots were involved alone, and in 9 cases, C5 to C6 nerve roots were involved together. The T2 signal intensity of the affected nerve increased, and 19 cases showed thickened and smooth nerve root edges. Twelve cases showed uneven thickening and segmental stenosis of the involved nerve roots. The diagnostic accuracy, sensitivity, and specificity of MRN for NA were higher than those of EMG. Combining MRN and EMG could improve the sensitivity and specificity of diagnosis. CONCLUSION: The main feature of MRN in patients with NA was that it was unilateral brachial plexus asymmetric involvement. The diagnostic effect of MRN was better than that of EMG. The combined diagnosis of MRN and EMG can help clinicians diagnose NA accurately.

Learning from algorithm-generated pseudo-annotations for detecting ants in videos.

Deep learning (DL) based detection models are powerful tools for large-scale analysis of dynamic biological behaviors in video data. Supervised training of a DL detection model often requires a large amount of manually-labeled training data which are time-consuming and labor-intensive to acquire. In this paper, we propose LFAGPA (Learn From Algorithm-Generated Pseudo-Annotations) that utilizes (noisy) annotations which are automatically generated by algorithms to train DL models for ant detection in videos. Our method consists of two main steps: (1) generate foreground objects using a (set of) state-of-the-art foreground extraction algorithm(s); (2) treat the results from step (1) as pseudo-annotations and use them to train deep neural networks for ant detection. We tackle several challenges on how to make use of automatically generated noisy annotations, how to learn from multiple annotation resources, and how to combine algorithm-generated annotations with human-labeled annotations (when available) for this learning framework. In experiments, we evaluate our method using 82 videos (totally 20,348 image frames) captured under natural conditions in a tropical rain-forest for dynamic ant behavior study. Without any manual annotation cost but only algorithm-generated annotations, our method can achieve a decent detection performance (77% in [Formula: see text] score). Moreover, when using only 10% manual annotations, our method can train a DL model to perform as well as using the full human annotations (81% in [Formula: see text] score).