A spatial transformation-based CAN model for information integration within grid cell modules.

The hippocampal-entorhinal circuit is considered to play an important role in the spatial cognition of animals. However, the mechanism of the information flow within the circuit and its contribution to the function of the grid-cell module are still topics of discussion. Prevailing theories suggest that grid cells are primarily influenced by self-motion inputs from the Medial Entorhinal Cortex, with place cells serving a secondary role by contributing to the visual calibration of grid cells. However, recent evidence suggests that both self-motion inputs and visual cues may collaboratively contribute to the formation of grid-like patterns. In this paper, we introduce a novel Continuous Attractor Network model based on a spatial transformation mechanism. This mechanism enables the integration of self-motion inputs and visual cues within grid-cell modules, synergistically driving the formation of grid-like patterns. From the perspective of individual neurons within the network, our model successfully replicates grid firing patterns. From the view of neural population activity within the network, the network can form and drive the activated bump, which describes the characteristic feature of grid-cell modules, namely, path integration. Through further exploration and experimentation, our model can exhibit significant performance in path integration. This study provides a new insight into understanding the mechanism of how the self-motion and visual inputs contribute to the neural activity within grid-cell modules. Furthermore, it provides theoretical support for achieving accurate path integration, which holds substantial implications for various applications requiring spatial navigation and mapping.

Cinquefoil Knot Possessing Dynamic and Tunable Metal Coordination.

While the majority of knots are made from the metal-template approach, the use of entangled, constrained knotted loops to modulate the coordination of the metal ions remains inadequately elucidated. Here, we report on the coordination chemistry of a 140-atom-long cinquefoil knotted strand comprising five tridentate and five bidentate chelating vacancies. The knotted loop is prepared through the self-assembly of asymmetric "3 + 2" dentate ligands with copper(II) ions that favor five-coordination geometry. The formation of the copper(II) pentameric helicate is confirmed by X-ray crystallography, while the corresponding copper(II) knot is characterized by XPS and LR-/HR ESI-MS. Upon removal of the original template, the knotted ligand facilitates zinc(II) ions, which typically form four- or six-coordination geometries, resulting in the formation of an otherwise inaccessible zinc(II) metallic knot with coordinatively unsaturated metal centers. The coordination numbers and geometries of the zinc(II) cations are undoubtedly determined by X-ray crystallography. Despite the kinetically labile nature and high reversibility of the zinc(II) complex preventing the detection of 5-to-6 coordination equilibrium in solution, the effects on metal-ion coordination induced by knotting hold promise for fine-tuning the coordination of metal complexes.

SPH7854, a gut-limited RORγt antagonist, ameliorates TNBS-induced experimental colitis in rat.

Multiple lines of evidence suggest that Retinoic Acid Related Orphan Nuclear Receptor gamma t (RORγt) is a potent therapeutic target for inflammatory bowel disease (IBD). However, systemic blockade of RORγt easily leads to thymic lymphoma and aberrant liver function. Therefore, the development of gut-limited RORγt antagonists may lead to the development of innovative IBD therapeutics that improve safety and retain effectiveness. We discovered SPH7854, a potent and selective RORγt antagonist. The effect of SPH7854 on the differentiation of T helper 1 (Th1)/Th17/regulatory T (Treg) cells was evaluated in mouse and human primary cells. SPH7854 (2-(4-(ethylsulfonyl)phenyl)-N- (6-(2-methyl-2-(pyridin-2-yl) propanoyl)pyridin-3-yl)acetamide) dose-dependently inhibited interleukin-17A (IL-17A) secretion from mouse CD4 + T cells and human peripheral blood mononuclear cells (PBMC). Additionally, SPH7854 strongly suppressed Th17 cell differentiation and considerably promoted Treg cell differentiation while slightly affected Th1 cell differentiation from mouse CD4 + T cells. The pharmacokinetic (PK) studies indicated that SPH7854 was restricted to the gut: the bioavailability and maximal plasma concentration of SPH7854 after oral administration (6 mg/kg) were 1.24 ± 0.33 % and 4.92 ± 11.81 nM, respectively, in rats. Strikingly, oral administration of SPH7854 (5 mg/kg and 15 mg/kg) twice daily significantly alleviated 2, 4, 6-trinitrobenzensulfonic acid (TNBS)-induced colitis in rats. SPH7854, especially at 15 mg/kg, significantly alleviated symptoms and improved macroscopic signs and microscopic structure in rat colitis, with decreased colonic mucosal levels of IL-17A, IL-6, tumor necrosis factor α (TNFα), monocyte chemoattractant protein-1 (MCP-1) and myeloperoxidase (MPO). These evidences indicated that blockade of RORγt activity via a gut-limited antagonist may be an effective and safe therapeutic strategy for IBD treatment.

Machine learning-guided multi-site combinatorial mutagenesis enhances the thermostability of pectin lyase.

Enhancing the thermostability of enzymes is crucial for industrial applications. Methods such as directed evolution are often limited by the huge sequence space and combinatorial explosion, making it difficult to obtain optimal mutants. In recent years, machine learning (ML)-guided protein engineering has become an attractive tool because of its ability to comprehensively explore the sequence space of enzymes and discover superior mutants. This study employed ML to perform combinatorial mutation design on the pectin lyase PMGL-Ba from Bacillus licheniformis, aiming to improve its thermostability. First, 18 single-point mutants with enhanced thermostability were identified through semi-rational design. Subsequently, the initial library containing a small number of low-order mutants was utilized to construct an ML model to explore the combinatorial sequence space (theoretically 196,608 mutants) of single-point mutants. The results showed that the ML-predicted second library was successfully enriched with highly thermostable combinatorial mutants. After one iteration of learning, the best-performing combinatorial mutant in the third library, P36, showed a 67-fold and 39-fold increase in half-life at 75 °C and 80 °C, respectively, as well as a 2.1-fold increase in activity. Structural analysis and molecular dynamics simulations provided insights into the improved performance of the engineered enzyme.

Real-world safety profile of eculizumab: an analysis of FDA adverse event reporting system and systematic review of case reports.

BACKGROUND: Most of the safety data regarding eculizumab came from clinical trials, while its safety information in the real world is still limited. RESEARCH DESIGN AND METHODS: The data of eculizumab in the FDA Adverse Event Reporting System (FAERS) database (from the first quarter of 2007 to the first quarter of 2023) was collected and analyzed. The case reports of adverse drug reactions (ADRs) related to eculizumab in PubMed, Embase and Web of Science before May 2023 were systematically reviewed. RESULTS: A total of 464 ADRs of eculizumab were identified in the FAERS database. The top five ADRs with the highest proportional reporting ratio (PRR) are total complement activity decreased, extravascular hemolysis, hemoglobinuria, total complement activity increased and breakthrough hemolysis. Fifty-one cases of ADR related to eculizumab were identified from 44 publications. The number of reported cases of eculizumab associated Neisseria gonorrhoeae infection in case reports was observed to be comparable to the number of cases of Neisseria meningitidis infection. CONCLUSIONS: Clinicians must pay close attention to the risk of infections in patients receiving eculizumab, including severe N. meningitidis infection and other potentially fatal infections such as N. gonorrhoeae infection. In addition, The possible emergence of new ADRs should be vigilant during clinical medication.

In vitro evaluation of the biocompatibility and bioactivity of a SLM-fabricated NiTi alloy with superior tensile property.

Because nickel-titanium (NiTi) alloys have unique functions, such as superelasticity, shape memory, and hysteresis similar to bone in the loading-unloading cycles of their recoverable deformations. They likely offer good bone integration, a low loosening rate, individual customization, and ease of insertion. Due to the poor processability of NITI, traditional methods cannot manufacture NiTi products with complex shapes. Orthopedic NiTi implants need to show an adequate fracture elongation of at least 8%. Additive manufacturing can be used to prepare NiTi implants with complex structures and tunable porosity. However, as previously reported, additively manufactured NiTi alloys could only exhibit a maximum tensile fracture strain of 7%. In new reports, a selective laser melting (SLM)-NiTi alloy has shown greater tensile strain (15.6%). Nevertheless, due to the unique microstructure of additive manufacturing NiTi that differs from traditional NITI, the biocompatibility of SLM-NITI manufactured by this new process requires further evaluation In this study, the effects of the improved NiTi alloy on bone marrow mesenchymal stem cell (BMSC) proliferation, adhesion, and cell viability were investigated via in vitro studies. A commercial Ti-6Al-4V alloy was studied side-by-side for comparison. Like the Ti-6Al-4V alloy, the SLM-NiTi alloy exhibited low cytotoxicity toward BMSCs and similar effect on cell adhesion or cell viability. This study demonstrates that the new SLM-NiTi alloy, which has exhibited improved mechanical properties, also displays excellent biocompatibility. Therefore, this alloy may be a superior implant material in biomedical implantation.

Shared genetic architecture of cortical thickness alterations in major depressive disorder and schizophrenia.

BACKGROUND: Major depressive disorder (MDD) and schizophrenia (SCZ) are heritable brain disorders characterized by alterations in cortical thickness. However, the shared genetic basis for cortical thickness changes in these disorders remains unclear. METHODS: We conducted a systematic literature search on cortical thickness in MDD and SCZ through PubMed and Web of Science. A coordinate-based meta-analysis was performed to identify cortical thickness changes. Additionally, utilizing summary statistics from the largest genome-wide association studies for depression (Ncase = 268,615, Ncontrol = 667,123) and SCZ (Ncase = 53,386, Ncontrol = 77,258), we explored shared genomic loci using conjunctional false discovery rate (conjFDR) analysis. Transcriptome-neuroimaging association analysis was then employed to identify shared genes associated with cortical thickness alterations, and enrichment analysis was finally carried out to elucidate the biological significance of these genes. RESULTS: Our search yielded 34 MDD (Ncase = 1621, Ncontrol = 1507) and 19 SCZ (Ncase = 1170, Ncontrol = 1043) neuroimaging studies for cortical thickness meta-analysis. Specific alterations in the left supplementary motor area were observed in MDD, while SCZ exhibited widespread reductions in various brain regions, particularly in the frontal and temporal areas. The conjFDR approach identified 357 genomic loci jointly associated with MDD and SCZ. Within these loci, 55 genes were found to be associated with cortical thickness alterations in both disorders. Enrichment analysis revealed their involvement in nervous system development, apoptosis, and cell communication. CONCLUSION: This study revealed the shared genetic architecture underlying cortical thickness alterations in MDD and SCZ, providing insights into common neurobiological pathways. The identified genes and pathways may serve as potential transdiagnostic markers, informing precision medicine approaches in psychiatric care.

The galactomannan-EGCG physical complex: Effect of branching degree and molecular weight on structural and physiological properties.

Polysaccharides and polyphenols are bioactive components that co-exist in many plant foods. Their binary interaction in terms of the structure-function relationships, however, has not been well clarified. This study elucidated the correlation between the structural and physiological properties of galactomannan (GM) -catechin monomer complexes and GM with different branching or molecular weight (Mw). Results indicated that locus bean gum with lower branching degree (Gal/Man is 0.259) bound more readily to EGCG with adsorption rate of 19.42 %. EGCG and ECG containing galloyl groups were more inclined to form hydrogen bonds with GMs, significantly improving the adsorption by GMs. The introduction of EGCG could enhance the antioxidant activity and starch digestion inhibition of GM, which positively correlated with the adsorption capacity of EGCG. The guar gum (GG) with higher Mw (7384.3 kDa) could transport 71.51 % EGCG into the colon, while the retention rate of EGCG reaching the colon alone was only 46.33 %. Conversely, GM-EGCG complex with lower Mw (6.9 kDa) could be readily utilized by gut microbiota, and increased production of short-chain fatty acids (SCFAs). This study elucidated the structure-properties relationship of GM-EGCG complexes, and provide a new idea for the development and precision nutrition of polysaccharides-polyphenol complexes fortified functional foods.

Unraveling multi-scale neuroimaging biomarkers and molecular foundations for schizophrenia: A combined multivariate pattern analysis and transcriptome-neuroimaging association study.

AIMS: Schizophrenia is characterized by alterations in resting-state spontaneous brain activity; however, it remains uncertain whether variations at diverse spatial scales are capable of effectively distinguishing patients from healthy controls. Additionally, the genetic underpinnings of these alterations remain poorly elucidated. We aimed to address these questions in this study to gain better understanding of brain alterations and their underlying genetic factors in schizophrenia. METHODS: A cohort of 103 individuals with diagnosed schizophrenia and 110 healthy controls underwent resting-state functional MRI scans. Spontaneous brain activity was assessed using the regional homogeneity (ReHo) metric at four spatial scales: voxel-level (Scale 1) and regional-level (Scales 2-4: 272, 53, 17 regions, respectively). For each spatial scale, multivariate pattern analysis was performed to classify schizophrenia patients from healthy controls, and a transcriptome-neuroimaging association analysis was performed to establish connections between gene expression data and ReHo alterations in schizophrenia. RESULTS: The ReHo metrics at all spatial scales effectively discriminated schizophrenia from healthy controls. Scale 2 showed the highest classification accuracy at 84.6%, followed by Scale 1 (83.1%) and Scale 3 (78.5%), while Scale 4 exhibited the lowest accuracy (74.2%). Furthermore, the transcriptome-neuroimaging association analysis showed that there were not only shared but also unique enriched biological processes across the four spatial scales. These related biological processes were mainly linked to immune responses, inflammation, synaptic signaling, ion channels, cellular development, myelination, and transporter activity. CONCLUSIONS: This study highlights the potential of multi-scale ReHo as a valuable neuroimaging biomarker in the diagnosis of schizophrenia. By elucidating the complex molecular basis underlying the ReHo alterations of this disorder, this study not only enhances our understanding of its pathophysiology, but also pave the way for future advancements in genetic diagnosis and treatment of schizophrenia.

Memory-Augmented 3D Point Cloud Semantic Segmentation Network for Intelligent Mining Shovels.

The semantic segmentation of the 3D operating environment represents the key to intelligent mining shovels' autonomous digging and loading operation. However, the complexity of the operating environment of intelligent mining shovels presents challenges, including the variety of scene targets and the uneven number of samples. This results in low accuracy of 3D semantic segmentation and reduces the autonomous operation accuracy of the intelligent mine shovels. To solve these issues, this paper proposes a 3D point cloud semantic segmentation network based on memory enhancement and lightweight attention mechanisms. This model addresses the challenges of an uneven number of sampled scene targets, insufficient extraction of key features to reduce the semantic segmentation accuracy, and an insufficient lightweight level of the model to reduce deployment capability. Firstly, we investigate the memory enhancement learning mechanism, establishing a memory module for key semantic features of the targets. Furthermore, we address the issue of forgetting non-dominant target point cloud features caused by the unbalanced number of samples and enhance the semantic segmentation accuracy. Subsequently, the channel attention mechanism is studied. An attention module based on the statistical characteristics of the channel is established. The adequacy of the expression of the key features is improved by adjusting the weights of the features. This is done in order to improve the accuracy of semantic segmentation further. Finally, the lightweight mechanism is studied by adopting the deep separable convolution instead of conventional convolution to reduce the number of model parameters. Experiments demonstrate that the proposed method can improve the accuracy of semantic segmentation in the 3D scene and reduce the model's complexity. Semantic segmentation accuracy is improved by 7.15% on average compared with the experimental control methods, which contributes to the improvement of autonomous operation accuracy and safety of intelligent mining shovels.

Twenty-five years of research on resting-state fMRI of major depressive disorder: A bibliometric analysis of hotspots, nodes, bursts, and trends.

Major depressive disorder (MDD) is a debilitating mental health condition that poses significant risks and burdens. Resting-state functional magnetic resonance imaging (fMRI) has emerged as a promising tool in investigating the neural mechanisms underlying MDD. However, a comprehensive bibliometric analysis of resting-state fMRI in MDD is currently lacking. Here, we aimed to thoroughly explore the trends and frontiers of resting-state fMRI in MDD research. The relevant publications were retrieved from the Web of Science database for the period between 1998 and 2022, and the CiteSpace software was employed to identify the influence of authors, institutions, countries/regions, and the latest research trends. A total of 1501 publications met the search criteria, revealing a gradual increase in the number of annual publications over the years. China contributed the largest publication output, accounting for the highest percentage among all countries. Particularly, the University of Electronic Science and Technology of China, Capital Medical University, and Harvard Medical School were identified as key institutions that have made substantial contributions to this growth. Neuroimage, Biological Psychiatry, Journal of Affective Disorders, and Proceedings of the National Academy of Sciences of the United States of America are among the influential journals in the field of resting-state fMRI research in MDD. Burst keywords analysis suggest the emerging research frontiers in this field are characterized by prominent keywords such as dynamic functional connectivity, cognitive control network, transcranial brain stimulation, and childhood trauma. Overall, our study provides a systematic overview into the historical development, current status, and future trends of resting-state fMRI in MDD, thus offering a useful guide for researchers to plan their future research.

Production of Secreted Antibody in Baculovirus Expression Vector System.

Monoclonal antibodies have widespread applications in disease treatment and antigen detection. They are traditionally produced using mammalian cell expression system, which is not able to satisfy the increasing demand of these proteins at large scale. Baculovirus expression vector system (BEVS) is an attractive alternative platform for the production of biologically active monoclonal antibodies. In this chapter, we demonstrate the production of an HIV-1 broadly neutralizing antibody b12 in BEVS. The processes including transfer vector construction, recombinant baculovirus generation, and antibody production and detection are described.

TCID50 Assay: A Simple Method to Determine Baculovirus Titer.

There are many methods that can be used to determine the infectious titer of your baculovirus stock. The TCID50 method is a simple end-point dilution method that determines the amount of baculovirus virus needed to produce a cytopathic effect or kill 50% of inoculated insect cells. Serial dilutions of baculovirus stock are added to Sf9 cells cultivated in 96-well plates and 3-5 days after infection, cells are monitored for cell death or cytopathic effect. The titer can then be calculated by the Reed-Muench method as described in this method.

Aneuploidy underlies brefeldin A-induced antifungal drug resistance in Cryptococcus neoformans.

Cryptococcus neoformans is at the top of the list of "most wanted" human pathogens. Only three classes of antifungal drugs are available for the treatment of cryptococcosis. Studies on antifungal resistance mechanisms are limited to the investigation of how a particular antifungal drug induces resistance to a particular drug, and the impact of stresses other than antifungals on the development of antifungal resistance and even cross-resistance is largely unexplored. The endoplasmic reticulum (ER) is a ubiquitous subcellular organelle of eukaryotic cells. Brefeldin A (BFA) is a widely used chemical inducer of ER stress. Here, we found that both weak and strong selection by BFA caused aneuploidy formation in C. neoformans, mainly disomy of chromosome 1, chromosome 3, and chromosome 7. Disomy of chromosome 1 conferred cross-resistance to two classes of antifungal drugs: fluconazole and 5-flucytosine, as well as hypersensitivity to amphotericin B. However, drug resistance was unstable, due to the intrinsic instability of aneuploidy. We found overexpression of AFR1 on Chr1 and GEA2 on Chr3 phenocopied BFA resistance conferred by chromosome disomy. Overexpression of AFR1 also caused resistance to fluconazole and hypersensitivity to amphotericin B. Furthermore, a strain with a deletion of AFR1 failed to form chromosome 1 disomy upon BFA treatment. Transcriptome analysis indicated that chromosome 1 disomy simultaneously upregulated AFR1, ERG11, and other efflux and ERG genes. Thus, we posit that BFA has the potential to drive the rapid development of drug resistance and even cross-resistance in C. neoformans, with genome plasticity as the accomplice.

Emotionally-oriented design in museums: a case study of the Jewish Museum Berlin.

Objective: This study examines the intricate interplay between architectural design and visitor emotional responses at the Jewish Museum Berlin, focusing on how specific spatial elements such as the Holocaust Tower, Garden of Exile, The Voids, and The Axis elicit varied affective experiences. The research aims to extend the discourse on environmental psychology and architectural empathy, particularly within the context of memorial museums. Method: Employing a non-intrusive approach, the study gathered emotional response data using the Positive and Negative Affect Schedule (PANAS) from 113 museum visitors, with 102 valid responses analyzed. Environmental conditions such as light, sound, and spatial design were quantitatively measured to correlate with emotional responses captured at the end of visitors' tours across the designated museum spaces. Results: Findings revealed that architectural elements significantly influence emotional responses. High levels of negative emotions like fear and anxiety were markedly evident in the Holocaust Tower due to its minimal lighting and stark concrete structure. Conversely, the Garden of Exile induced more positive emotions through its use of natural light and greenery, emphasizing the role of biophilic design in enhancing emotional well-being. Statistical analysis supported these observations, with variations in emotional impact across different spaces demonstrating the profound effect of architectural design on visitor experiences. Conclusion: This study confirms that a variety of design elements and spatial strategies not only facilitate the presentation of historical narratives but also actively sculpt the emotional involvement and experiences of visitors. Our findings highlight the efficacy of emotionally-oriented architectural design in deepening the impact and engagement of museum visitors, emphasizing the transformative power of these environments in shaping visitor perceptions and interactions.

Prognostic value of angiographic microvascular resistance in patients with ST-segment elevation myocardial infarction.

BACKGROUND: The Angiographic Microvascular Resistance (AMR), derived from a solitary angiographic view, has emerged as a viable substitute for the Index of Microcirculatory Resistance (IMR). However, the prognostic significance in ST-Segment Elevation Myocardial Infarction (STEMI) patients is yet to be established. This research endeavors to explore the prognostic capabilities of AMR in patients diagnosed with STEMI. METHODS: In this single-center, retrospective study, 232 patients diagnosed with STEMI who received primary Percutaneous Coronary Intervention (PCI) were recruited from January 1, 2018, to June 30, 2022. Utilizing the maximally selected log-rank statistics analysis, participants were divided into two cohorts according to an AMR threshold of 2.55 mmHg*s/cm. The endpoint evaluated was a composite of all-cause mortality or hospital readmission due to heart failure. RESULTS: At a median follow-up of 1.74 (1.07, 3.65) years, the composite endpoint event was observed in 28 patients within the higher AMR group and 8 patients within the lower AMR group. The higher AMR group showed a significantly higher risk for composite outcome compared to those within the low-AMR group (HRadj: 3.33; 95% CI 1.30‒8.52; p = 0.03). AMR ≥ 2.55 mmHg*s/cm was an independent predictor of the composite endpoint (HR = 2.33; 95% CI 1.04‒5.21; p = 0.04). Furthermore, a nomogram containing age, sex, left ventricle ejection fraction, post-PCI Quantitative Flow Ratio (QFR), and AMR was developed and indicated a poorer prognosis in the high-risk group for STEMI patients at 3 years. (HR=4.60; 95% CI 1.91‒11.07; p < 0.01). CONCLUSIONS: AMR measured after PCI can predict the risk of all-cause death or readmission for heart failure in patients with STEMI. AMR-involved nomograms improved predictive performance over variables alone.

Moderate/severe biatrial dilation predicts adverse events after ablation in atrial fibrillation with heart failure.

AIMS: To retrospectively compare the long-term outcomes following atrial fibrillation (AF) ablation between heart failure (HF) with preserved ejection fraction (EF) (HFpEF) and reduced/mildly reduced EF (HFr-mrEF) patients, and to identify novel predictors of adverse clinical events. METHODS: In total, 1402 AF patients with HF who underwent successful ablation were consecutively enrolled. Adverse clinical events including all-cause death, HF hospitalization, and stroke were followed up. Cox proportional hazards models were used to assess the associations between clinical factors and events. Kaplan-Meier analysis was performed to estimate the cumulative incidences of these events. A receiver operating characteristic curve was used to test the ability of these predictors. RESULTS: During a follow-up period of 42 ± 15 months, 265 (18.9%) patients experienced adverse clinical events after ablation. The cumulative incidence of adverse clinical events was significantly higher in HFr-mrEF than in HFpEF (25.4% vs. 15.7%, P < 0.001), the similar tendency was observed on all-cause death (10.5% vs. 6.5%, P = 0.011) and HF hospitalization (17.2% vs. 10.1%, P < 0.001). After multivariate adjustment, non-paroxysmal AF [hazard ratio (HR) 1.922, 95% confidence interval (CI) 1.130-3.268, P = 0.016], LAD ≥ 45 mm (HR 2.197, 95% CI 1.206-4.003, P < 0.001), LVEF (HR 0.959, 95% CI 0.946-0.981, P < 0.001), and RAD ≥ 45 mm (HR 2.044, 95% CI 1.362-3.238, P < 0.001) remained the independent predictors for developing adverse clinical events. A predictive model performed with non-paroxysmal AF, LAD ≥ 45 mm and RAD ≥ 45 mm yielded an area under curve of 0.728 (95% CI 0.696-0.760, P < 0.001). CONCLUSIONS: AF patients with HFpEF had better long-term outcomes than those with HFr-mrEF, and moderate/severe biatrial dilation could predict adverse clinical events following catheter ablation in AF and HF patients.

Dual-Function Wearable Hydrogel Optical Fiber for Monitoring Posture and Sweat pH.

In recent years, wearable devices have been widely used for human health monitoring. Such monitoring predominantly relies on the principles of optics and electronics. However, electronic detection is susceptible to electromagnetic interference, and traditional optical fiber detection is limited in functionality and unable to simultaneously detect both physical and chemical signals. Hence, a wearable, embedded asymmetric color-blocked optical fiber sensor based on a hydrogel has been developed. Its sensing principle is grounded in the total internal reflection within the optical fiber. The method for posture sensing involves changes in the light path due to fiber bending with color blocks providing wavelength-selective modulation by absorption changes. Sweat pH sensing is facilitated by variations in fluorescence intensity triggered by sweat-induced conformational changes in Rhodamine B. With just one fiber, it achieves both physical and chemical signal detection. Fabricated using a molding technique, this fiber boasts excellent biocompatibility and can accurately discern single and multiple bending points, with a recognition range of 0-90° for a single segment, a detection limit of 0.02 mm-1 and a sweat pH sensing linear regression R2 of 0.993, alongside great light propagation properties (-0.6 dB·cm-1). With its extensive capabilities, it holds promise for applications in medical monitoring.

NGS panel enhance precise diagnosis of myeloid neoplasms under WHO-HAEM5 and International Consensus Classification: An observational study.

This study aimed to assess hematological diseases next-generation sequencing (NGS) panel enhances the diagnosis and classification of myeloid neoplasms (MN) using the 5th edition of the WHO Classification of Hematolymphoid Tumors (WHO-HAEM5) and the International Consensus Classification (ICC) of Myeloid Tumors. A cohort of 112 patients diagnosed with MN according to the revised fourth edition of the WHO classification (WHO-HAEM4R) underwent testing with a 141-gene NGS panel for hematological diseases. Ancillary studies were also conducted, including bone marrow cytomorphology and routine cytogenetics. The cases were then reclassified according to WHO-HAEM5 and ICC to assess the practical impact of these 2 classifications. The mutation detection rates were 93% for acute myeloid leukemia (AML), 89% for myelodysplastic syndrome (MDS), 94% for myeloproliferative neoplasm (MPN), and 100% for myelodysplasia/myeloproliferative neoplasm (MDS/MPN) (WHO-HAEM4R). NGS provided subclassified information for 26 and 29 patients with WHO-HAEM5 and ICC, respectively. In MPN, NGS confirmed diagnoses in 16 cases by detecting JAK2, MPL, or CALR mutations, whereas 13 "triple-negative" MPN cases revealed at least 1 mutation. NGS panel testing for hematological diseases improves the diagnosis and classification of MN. When diagnosed with ICC, NGS produces more classification subtype information than WHO-HAEM5.

Modeling the grid cell activity based on cognitive space transformation.

The grid cells in the medial entorhinal cortex are widely recognized as a critical component of spatial cognition within the entorhinal-hippocampal neuronal circuits. To account for the hexagonal patterns, several computational models have been proposed. However, there is still considerable debate regarding the interaction between grid cells and place cells. In response, we have developed a novel grid-cell computational model based on cognitive space transformation, which established a theoretical framework of the interaction between place cells and grid cells for encoding and transforming positions between the local frame and global frame. Our model not only can generate the firing patterns of the grid cells but also reproduces the biological experiment results about the grid-cell global representation of connected environments and supports the conjecture about the underlying reason. Moreover, our model provides new insights into how grid cells and place cells integrate external and self-motion cues.