GroupFormer for hyperspectral image classification through group attention.

Hyperspectral image (HSI) data has a wide range of valuable spectral information for numerous tasks. HSI data encounters challenges such as small training samples, scarcity, and redundant information. Researchers have introduced various research works to address these challenges. Convolution Neural Network (CNN) has gained significant success in the field of HSI classification. CNN's primary focus is to extract low-level features from HSI data, and it has a limited ability to detect long-range dependencies due to the confined filter size. In contrast, vision transformers exhibit great success in the HSI classification field due to the use of attention mechanisms to learn the long-range dependencies. As mentioned earlier, the primary issue with these models is that they require sufficient labeled training data. To address this challenge, we proposed a spectral-spatial feature extractor group attention transformer that consists of a multiscale feature extractor to extract low-level or shallow features. For high-level semantic feature extraction, we proposed a group attention mechanism. Our proposed model is evaluated using four publicly available HSI datasets, which are Indian Pines, Pavia University, Salinas, and the KSC dataset. Our proposed approach achieved the best classification results in terms of overall accuracy (OA), average accuracy (AA), and Kappa coefficient. As mentioned earlier, the proposed approach utilized only 5%, 1%, 1%, and 10% of the training samples from the publicly available four datasets.

Advanced federated ensemble internet of learning approach for cloud based medical healthcare monitoring system.

Medical image machines serve as a valuable tool to monitor and diagnose a variety of diseases. However, manual and centralized interpretation are both error-prone and time-consuming due to malicious attacks. Numerous diagnostic algorithms have been developed to improve precision and prevent poisoning attacks by integrating symptoms, test methods, and imaging data. But in today's digital technology world, it is necessary to have a global cloud-based diagnostic artificial intelligence model that is efficient in diagnosis and preventing poisoning attacks and might be used for multiple purposes. We propose the Healthcare Federated Ensemble Internet of Learning Cloud Doctor System (FDEIoL) model, which integrates different Internet of Things (IoT) devices to provide precise and accurate interpretation without poisoning attack problems, thereby facilitating IoT-enabled remote patient monitoring for smart healthcare systems. Furthermore, the FDEIoL system model uses a federated ensemble learning strategy to provide an automatic, up-to-date global prediction model based on input local models from the medical specialist. This assures biomedical security by safeguarding patient data and preserving the integrity of diagnostic processes. The FDEIoL system model utilizes local model feature selection to discriminate between malicious and non-malicious local models, and ensemble strategies use positive and negative samples to optimize the performance of the test dataset, enhancing its capability for remote patient monitoring. The FDEIoL system model achieved an exceptional accuracy rate of 99.24% on the Chest X-ray dataset and 99.0% on the MRI dataset of brain tumors compared to centralized models, demonstrating its ability for precision diagnosis in IoT-enabled healthcare systems.

Investigation of the Cyclohexene Oxidation Mechanism Through the Direct Measurement of Organic Peroxy Radicals.

Monoterpenes, the second most abundant biogenic volatile organic compounds globally, are crucial in forming secondary organic aerosols, making their oxidation mechanisms vital for addressing climate change and air pollution. This study utilized cyclohexene as a surrogate to explore first-generation products from its ozonolysis through laboratory experiments and mechanistic modeling. We employed proton transfer reaction mass spectrometry with NH4+ ion sources (NH4+-CIMS) and a custom-built OH calibration source to quantify organic peroxy radicals (RO2) and closed-shell species. Under near-real atmospheric conditions in a Potential Aerosol Mass-Oxidation Flow Reactor, we identified 30 ozonolysis products, expanding previous data sets of low-oxygen compounds. Combined with simulations based on the Generator for Explicit Chemistry and Kinetics of Organics in the Atmosphere and relevant literature, our results revealed that OH dominates over ozone in cyclohexene oxidation at typical atmospheric oxidant levels with H-abstraction contributing 30% of initial RO2 radicals. Highly oxidized molecules primarily arise from RO2 autoxidation initiated by ozone, and at least 15% of ozone oxidation products follow the overlooked nonvinyl hydroperoxides pathway. Gaps remain especially in understanding RO2 cross-reactions, and the structural complexity of monoterpenes further complicates research. As emissions decrease and afforestation increases, understanding these mechanisms becomes increasingly critical.

Finely ordered intracellular domain harbors an allosteric site to modulate physiopathological function of P2X3 receptors.

P2X receptors, a subfamily of ligand-gated ion channels activated by extracellular ATP, are implicated in various physiopathological processes, including inflammation, pain perception, and immune and respiratory regulations. Structural determinations using crystallography and cryo-EM have revealed that the extracellular three-dimensional architectures of different P2X subtypes across various species are remarkably identical, greatly advancing our understanding of P2X activation mechanisms. However, structural studies yield paradoxical architectures of the intracellular domain (ICD) of different subtypes (e.g., P2X3 and P2X7) at the apo state, and the role of the ICD in P2X functional regulation remains unclear. Here, we propose that the P2X3 receptor's ICD has an apo state conformation similar to the open state but with a less tense architecture, containing allosteric sites that influence P2X3's physiological and pathological roles. Using covalent occupancy, engineered disulfide bonds and voltage-clamp fluorometry, we suggested that the ICD can undergo coordinated motions with the transmembrane domain of P2X3, thereby facilitating channel activation. Additionally, we identified a novel P2X3 enhancer, PSFL77, and uncovered its potential allosteric site located in the 1α3ß domain of the ICD. PSFL77 modulated pain perception in P2rx3+/+, but not in P2rx3-/-, mice, indicating that the 1α3ß, a "tunable" region implicated in the regulation of P2X3 functions. Thus, when P2X3 is in its apo state, its ICD architecture is fairly ordered rather than an unstructured outward folding, enabling allosteric modulation of the signaling of P2X3 receptors.

Unclassical Radical Generation Mechanisms in the Troposphere: A Review.

Hydroxyl (OH) and hydroperoxyl (HO2) radicals, collectively known as HOx radicals, are crucial in removing primary pollutants, controlling atmospheric oxidation capacity, and regulating global air quality and climate. An imbalance between radical observations and simulations has been identified based on radical closure experiments, a valuable tool for accessing the state-of-the-art chemical mechanisms, demonstrating a deviation between the existing and actual tropospheric mechanisms. In the past decades, researchers have attempted to explain this deviation and proposed numerous radical generation mechanisms. However, these newly proposed unclassical radical generation mechanisms have not been systematically reviewed, and previous radical-related reviews dominantly focus on radical measurement instruments and radical observations in extensive field campaigns. Herein, we overview the unclassical generation mechanisms of radicals, mainly focusing on outlining the methodology and results of radical closure experiments worldwide and systematically introducing the mainstream mechanisms of unclassical radical generation, involving the bimolecular reaction of HO2 and organic peroxy radicals (RO2), RO2 isomerization, halogen chemistry, the reaction of H2O with O2 over soot, epoxide formation mechanism, mechanism of electronically excited NO2 and water, and prompt HO2 formation in aromatic oxidation. Finally, we highlight the existing gaps in the current studies and suggest possible directions for future research. This review of unclassical radical generation mechanisms will help promote a comprehensive understanding of the latest radical mechanisms and the development of additional new mechanisms to further explain deviations between the existing and actual mechanisms.

Severe hypoglycaemia-induced microglial inflammation damages microvascular endothelial cells, leading to retinal destruction.

Human microglia (HMC) are stress-induced inflammatory cells of the retina. It is unknown whether severe hypoglycaemia causes inflammation in microglia, affects the permeability of human retinal microvascular endothelial cells (HRMECs), and causes retinal damage. This study aimed to explore the effects of severe hypoglycaemia on retinal microglial inflammation and endothelial cell permeability and evaluate the damage caused by hypoglycaemia to the retina. The CCK-8 assay was used to measure cell viability. Western blotting was used to detect IL-1ß, IL-6, TNF- α, claudin-1, and occludin expression. ELISA was used to detect IL-1ß, IL-6, and TNF- α. Transmission electron microscopy (TEM) and haematoxylin and eosin staining were used to observe the retinal structure. Immunohistochemistry and immunofluorescence staining assays were also used to detect IL-1ß, IL-6, TNF- α, claudin-1, and occludin expression. Severe hypoglycaemia promoted inflammation in HMC3 cells. Inflammation caused by hypoglycaemia leads to the decreased expression of tight junction proteins. In vivo, severe hypoglycaemia induced structural damage to the retina, increased the expression of inflammatory factors, and decreased the expression of tight junction proteins. Our results suggest that severe hypoglycaemia leads to acute retinal inflammation, affecting the permeability of HRMECs and causing retinal damage.

Ozone production sensitivity analysis for the Chengdu Plain Urban Agglomeration based on a multi-site and two-episode observation.

Chengdu Plain Urban Agglomeration (CPUA) is one of the most serious areas suffering from ozone pollution in China. A comprehensive field observation focused on the ozone production rate and its sensitivity was conducted at CPUA in the summer of 2019. Six sampling sites were set and two ozone pollution episodes were recognized. The daily maximum 8-h average (MDA8) O3 concentration reached 137.9 ppbv in the urban sites during the ozone pollution episode. Peak concentration of O3 was closely related to intense solar radiation, high temperatures, and precursor emissions. The OH-HO2-RO2 radical chemistry and ozone production rate (P(O3)) were calculated using an observation-based model (OBM). The daily peak OH concentration varied in the range of 3-13 × 106 molecules cm-3, and peak HO2 and RO2 were in the range of 2-14 × 108 molecules cm-3 during ozone pollution episodes. During the ozone pollution episode, the average maximum of P(O3) in suburban sites (about 30 ppbv h-1.) was compared with urban sites, and the maximum of P(O3) was 18 ppbv h-1 in rural sites. The relative incremental reactivity (RIR) results demonstrate that it was a VOCs-limited regime in the central urban area of Chengdu, with NOx suppression effect in some regions. In the southern neighboring suburb of Chengdu, it was VOCs-limited as well. However, the northern suburban area was a transition region. In the remote rural areas of the southern CPUA, it was highly NOx-limited. Local ozone production driven by the photochemical process is crucial to the ozone pollution formation in CPUA. The geographically differentiated recognition of the ozone regime found by this study can help to tailor control strategies for local conditions and avoid the negative effects of a one-size-fits-all approach.

Genome-Wide Identification and Bioinformatics Analysis of the FK506 Binding Protein Family in Rice.

The FK506 Binding Protein (FKBP), ubiquitously present across diverse species, is characterized by its evolutionarily conserved FK506 binding domain (FKBd). In plants, evidence suggests that this gene family plays integral roles in regulating growth, development, and responses to environmental stresses. Notably, research on the identification and functionality of FKBP genes in rice remains limited. Therefore, this study utilized bioinformatic tools to identify 30 FKBP-encoding genes in rice. It provides a detailed analysis of their chromosomal locations, evolutionary relationships with the Arabidopsis thaliana FKBP family, and gene structures. Further analysis of the promoter elements of these rice FKBP genes revealed a high presence of stress-responsive elements. Quantitative PCR assays under drought and heat stress conditions demonstrated that genes OsFKBP15-2, OsFKBP15-3, OsFKBP16-3, OsFKBP18, and OsFKBP42b are inducible by these adverse conditions. These findings suggest a significant role for the rice FKBP gene family in stress adaptation. This research establishes a critical foundation for deeper explorations of the functional roles of the OsFKBP genes in rice.

Radical chemistry and VOCs-NOx-O3-nitrate sensitivity in the polluted atmosphere of a suburban site in the North China Plain.

In this study, the chemical mechanisms of O3 and nitrate formation as well as the control strategy were investigated based on extensive observations in Tai'an city in the NCP and an observation-constrained box model. The results showed that O3 pollution was severe with the maximum hourly O3 concentration reaching 150 ppb. Higher O3 concentration was typically accompanied by higher PM2.5 concentrations, which could be ascribed to the common precursors of VOCs and NOx. The modeled averaged peak concentrations of OH, HO2, and RO2 were relatively higher compared to previous observations, indicating strong atmospheric oxidation capacity in the study area. The ROx production rate increased from 2.8 ppb h-1 to 5 ppb h-1 from the clean case to the heavily polluted case and was dominated by HONO photolysis, followed by HCHO photolysis. The contribution of radical-self combination to radical termination gradually exceeded NO2 + OH from clean to polluted cases, indicating that O3 formation shifted to a more NOx-limited regime. The O3 production rate increased from 14 ppb h-1 to 22 ppb h-1 from clean to heavily polluted cases. The relative incremental reactivity (RIR) results showed that VOCs and NOx had comparable RIR values during most days, which suggested that decreasing VOCs or NOx was both effective in alleviating O3 pollution. In addition, HCHO, with the largest RIR value, made important contribution to O3 production. The Empirical Kinetic Modeling Approach (EKMA) revealed that synergistic control of O3 and nitrate can be achieved by decreasing both NOx and VOCs emissions (e.g., alkenes) with the ratio of 3:1. This study emphasized the importance of NOx abatement for the synergistic control of O3 and nitrate pollution in the Tai'an area as the sustained emissions control has shifted the O3 and nitrate formation to a more NOx-limited regime.

Superior detection of low-allele burden Janus kinase 2 V617F mutation and monitoring clonal evolution in myeloproliferative neoplasms using chip-based digital PCR.

The JAK2 V617F is a prevalent driver mutation in Philadelphia chromosome-negative myeloproliferative neoplasms (Ph-MPNs), significantly affecting disease progression, immunophenotype, and patient outcomes. The World Health Organization (WHO) guidelines highlight the JAK2 V617F mutation as one of the key diagnostic criterions for Ph-MPNs. In this study, we analyzed 283 MPN samples with the JAK2 V617F mutation to assess the effectiveness of three detection technologies: chip-based digital PCR (cdPCR), real-time quantitative PCR (qPCR), and next-generation sequencing (NGS). Additionally, we investigated the relationship between JAK2 V617F mutant allele burden (% JAK2 V617F) and various laboratory characteristics to elucidate potential implications in MPN diagnosis. Our findings demonstrated high conformance of cdPCR with qPCR/NGS for detecting % JAK2 V617F, but the mutant allele burdens detected by qPCR/NGS were lower than those detected by cdPCR. Moreover, the cdPCR exhibited high sensitivity with a limit of detection (LoD) of 0.08% and a limit of quantification (LoQ) of 0.2% for detecting % JAK2 V617F in MPNs. Clinical implications were explored by correlating % JAK2 V617F with various laboratory characteristics in MPN patients, revealing significant associations with white blood cell counts, lactate dehydrogenase levels, and particularly ß2-microglobulin (ß2-MG) levels. Finally, a case report illustrated the application of cdPCR in detecting low-allele burdens in a de novo chronic myeloid leukemia (CML) patient with a hidden JAK2 V617F subclone, which expanded during tyrosine kinase inhibitor (TKI) treatment. Our findings underscore the superior sensitivity and accuracy of cdPCR, making it a valuable tool for early diagnosis and monitoring clonal evolution.

Atmospheric Oxidation Capacity Elevated during 2020 Spring Lockdown in Chengdu, China: Lessons for Future Secondary Pollution Control.

This study presents the measurement of photochemical precursors during the lockdown period from January 23, 2020, to March 14, 2020, in Chengdu in response to the coronavirus (COVID-19) pandemic. To derive the lockdown impact on air quality, the observations are compared to the equivalent periods in the last 2 years. An observation-based model is used to investigate the atmospheric oxidation capacity change during lockdown. OH, HO2, and RO2 concentrations are simulated, which are elevated by 42, 220, and 277%, respectively, during the lockdown period, mainly due to the reduction in nitrogen oxides (NOx). However, the radical turnover rates, i.e., OH oxidation rate L(OH) and local ozone production rate P(O3), which determine the secondary intermediates formation and O3 formation, only increase by 24 and 48%, respectively. Therefore, the oxidation capacity increases slightly during lockdown, which is partly attributed to unchanged alkene concentrations. During the lockdown, alkene ozonolysis seems to be a significant radical primary source due to the elevated O3 concentrations. This unique data set during the lockdown period highlights the importance of controlling alkene emission to mitigate secondary pollution formation in Chengdu and may also be applicable in other regions of China given an expected NOx reduction due to the rapid transformation to electrified fleets in the future.

Reducing Soil-Emitted Nitrous Acid as a Feasible Strategy for Tackling Ozone Pollution.

Severe ozone (O3) pollution has been a major air quality issue and affects environmental sustainability in China. Conventional mitigation strategies focusing on reducing volatile organic compounds and nitrogen oxides (NOx) remain complex and challenging. Here, through field flux measurements and laboratory simulations, we observe substantial nitrous acid (HONO) emissions (FHONO) enhanced by nitrogen fertilizer application at an agricultural site. The observed FHONO significantly improves model performance in predicting atmospheric HONO and leads to regional O3 increases by 37%. We also demonstrate the significant potential of nitrification inhibitors in reducing emissions of reactive nitrogen, including HONO and NOx, by as much as 90%, as well as greenhouse gases like nitrous oxide by up to 60%. Our findings introduce a feasible concept for mitigating O3 pollution: reducing soil HONO emissions. Hence, this study has important implications for policy decisions related to the control of O3 pollution and climate change.

Reactive aldehyde chemistry explains the missing source of hydroxyl radicals.

Hydroxyl radicals (OH) determine the tropospheric self-cleansing capacity, thus regulating air quality and climate. However, the state-of-the-art mechanisms still underestimate OH at low nitrogen oxide and high volatile organic compound regimes even considering the latest isoprene chemistry. Here we propose that the reactive aldehyde chemistry, especially the autoxidation of carbonyl organic peroxy radicals (R(CO)O2) derived from higher aldehydes, is a noteworthy OH regeneration mechanism that overwhelms the contribution of the isoprene autoxidation, the latter has been proved to largely contribute to the missing OH source under high isoprene condition. As diagnosed by the quantum chemical calculations, the R(CO)O2 radicals undergo fast H-migration to produce unsaturated hydroperoxyl-carbonyls that generate OH through rapid photolysis. This chemistry could explain almost all unknown OH sources in areas rich in both natural and anthropogenic emissions in the warm seasons, and may increasingly impact the global self-cleansing capacity in a future low nitrogen oxide society under carbon neutrality scenarios.

Dapagliflozin ameliorated retinal vascular permeability in diabetic retinopathy rats by suppressing inflammatory factors.

BACKGROUND: Diabetic retinopathy is a common microvascular complication of diabetes and one of the major causes of blindness in the working-age population. Emerging evidence has elucidated that inflammation drives the key mechanism of diabetes-mediated retinal disturbance. As a new therapeutic drug targeting diabetes, whether dapagliflozin could improve vascular permeability from the perspective of anti-inflammatory effect need to be further explored. METHODS: Type 2 diabetic retinopathy rat model was established and confirmed by fundus fluorescein angiography (FFA). ELISA detected level of plasma inflammatory factors and C-peptide. HE staining, immunohistochemistry and western blot detected histopathology changes of retina, expression of retinal inflammatory factors and tight junction proteins. RESULTS: Dapagliflozin exhibited hypoglycemic effect comparable to insulin, but did not affect body weight. By inhibiting expression of inflammatory factors (NLRP3, Caspase-1, IL-18, NF-κB) in diabetic retina and plasma, dapagliflozin reduced damage of retinal tight junction proteins and improved retinal vascular permeability. The anti-inflammatory effect of dapagliflozin was superior to insulin. CONCLUSIONS: Dapagliflozin improved retinal vascular permeability by reducing diabetic retinal and plasma inflammatory factors. The anti-inflammatory mechanism of dapagliflozin is independent of hypoglycemic effect and superior to insulin.

Septins provide microenvironment sensing and cortical actomyosin partitioning in motile amoeboid T lymphocytes.

The all-terrain motility of lymphocytes in tissues and tissue-like gels is best described as amoeboid motility. For amoeboid motility, lymphocytes do not require specific biochemical or structural modifications to the surrounding extracellular matrix. Instead, they rely on changing shape and steric interactions with the microenvironment. However, the exact mechanism of amoeboid motility remains elusive. Here, we report that septins participate in amoeboid motility of T cells, enabling the formation of F-actin and α-actinin-rich cortical rings at the sites of cell cortex-indenting collisions with the extracellular matrix. Cortical rings compartmentalize cells into chains of spherical segments that are spatially conformed to the available lumens, forming transient "hourglass"-shaped steric locks onto the surrounding collagen fibers. The steric lock facilitates pressure-driven peristaltic propulsion of cytosolic content by individually contracting cell segments. Our results suggest that septins provide microenvironment-guided partitioning of actomyosin contractility and steric pivots required for amoeboid motility of T cells in tissue-like microenvironments.

Association between area under the C-peptide curve during an oral glucose tolerance test and diabetic retinopathy in type 2 diabetes patients.

AIMS/INTRODUCTION: To evaluate the relative contributions of the area under the C-peptide curve (AUCC ) in diabetic retinopathy (DR) during an oral glucose tolerance test and C-peptide release test in patients with type 2 diabetes. MATERIALS AND METHODS: We retrospectively analyzed the data of 969 patients. Their general characteristics were retrieved. A series of parameters for assessing pancreatic ß-cells function, such as the AUCC for six time periods: 0-60 min (AUCC0-60 ), 0-120 min (AUCC0-120 ), 0-180 min (AUCC0-180 ), 60-120 min (AUCC60-120 ), 60-180 min (AUCC60-180 ) and 120-180 min (AUCC120-180 ); the area under the glucose-time curve for six time periods: 0-60 min (AUCG0-60 ), 0-120 min (AUCG0-120 ), 0-180 min (AUCG0-180 ), 60-120 min (AUCG60-120 ), 60-180 min (AUCG60-180 ) and 120-180 min (AUCG120-180 ) and their related indexes, were calculated through 0-180 min oral glucose tolerance test and C-peptide release test. We used univariate analysis to examine the potential factors affecting DR. Spearman's correlation was used to analyze the correlation between AUCC -related indexes and DR. The logistic regression model was used to investigate AUCC and its related indexes' contribution to incidence DR. A smooth curve fitting model was used to determine the correlation, non-linear relationship, and threshold effect between AUCC and DR. RESULTS: Of the 969 patients with type 2 diabetes, 469 (48.40%) and 500 (51.60%) were classified as the DR group and non-DR group. Compared with the non-DR group, the DR patients had lower AUCC and AUCC /AUCG . Spearman's correlation analysis showed that AUCC -related indexes were all negatively correlated with DR. The logistic regression analysis determined that there were associations between AUCC and DR in the adjusted models. The odds ratio values of AUCC0-60 , AUCC0-120 , AUCC0-180 , AUCC0-60 /AUCG0-60 , AUCC0-120 /AUCG0-120 , AUCC0-180 /AUCG0-180 , AUCC60-120 , AUCC60-180 , AUCC120-180 , AUCC60-120 /AUCG60-120 , AUCC60-180 /AUCG60-180 and AUCC120-180 /AUCG120-180 were 0.817 (0.750, 0.890), 0.925 (0.895, 0.955), 0.951 (0.932, 0.970), 0.143 (0.060, 0.340), 0.194 (0.093, 0.406), 0.223 (0.116, 0.427), 0.886 (0.842, 0.933), 0.939 (0.915, 0.963), 0.887 (0.846, 0.930), 0.253 (0.133, 0.479), 0.282 (0.160, 0.497) and 0.355 (0.220, 0.573), respectively. AUCC showed a non-linear relationship with DR, with an inflection point. The inflection points of AUCC180 /AUCG180 , AUCC60-120 , AUCC60-180 , AUCC120-180 , AUCC60-120 /AUCG60-120 , AUCC60-180 /AUCG60-180 , AUCC120-180 /AUCG120-180 and DR were 17.51, 0.542, 6.6, 15.7, 8.23, 0.534, 0.593 and 0.808 (P < 0.0001). When the indexes related to the AUCC were less than the inflection point value, they were significantly negatively associated with DR. CONCLUSIONS: The indexes related to the AUCC for six time periods during an oral glucose tolerance test and C-peptide release test was closely associated with the incidence to DR in patients with type 2 diabetes. AUCC has the added advantage of being a cheap and convenient risk assessment over traditional ophthalmic screening.

Effects of mulberry twig alkaloids(Sangzhi alkaloids) and metformin on blood glucose fluctuations in combination with premixed insulin-treated patients with type 2 diabetes.

Introduction: We aimed to evaluated the effect of premixed insulin (Ins), premixed insulin combined with metformin (Ins+Met) or mulberry twig alkaloids(Ins+SZ-A) on blood glucose fluctuations in patients with type 2 diabetes (T2DM) using continuous glucose monitors (CGM). Methods: Thirty patients with T2DM and poor blood glucose control using drugs were evaluated for eligibility during the screening period. Subsequently, their original hypoglycemic drugs were discontinued during the lead-in period, and after receiving Ins intensive treatment for 2 weeks, they were randomly assigned to receive either Ins, Ins+Met, or Ins+SZ-A treatment for the following 12 weeks. The main efficacy endpoint comprised changes in their CGM indicators changes (mean blood glucose level [MBG], standard deviation of blood glucose [SDBG], mean amplitude of glycemic excursions [MAGE], postprandial glucose excursions [PPGE], the largest amplitude of glycemic excursions [LAGE], mean of daily difference [MODD], time in range between 3.9-10.0 mmol/L [TIR] and area under the curve for each meal [AUCpp]) during the screening, lead-in, and after 12-week treatment period. Changes in glycosylated hemoglobin (HbA1c), fasting blood glucose (FBG), 1-h postprandial blood glucose (1h-PBG), 2-h postprandial blood glucose (2h-PBG), fasting blood lipids and postprandial blood lipids were also measured at baseline and after 12 weeks of treatment. Results: The CGM indicators of the three groups during the lead-in period all showed significant improvements compared to the screening period (P<0.05). Compared with those in the lead-in period, all of the CGM indicators improved in the the Ins+Met and Ins+SZ-A groups after 12 weeks of treatment (P<0.05), except for MODD. After 12-week treatment, compared with the Ins group, Ins+Met and Ins+SZ-A groups showed improved MBG, SDBG, TIR, breakfast AUCpp,lunch AUCpp, HbA1c, FBG, 1h-PBG, fasting blood lipid and postprandial blood lipid indicators (P<0.05). Further, the LAGE, PPGE, MAGE, dinner AUCpp and 2h-PBG levels of the Ins+SZ-A group were significantly lower than those of the Ins+Met and Ins groups (P<0.05). Conclusion: Our findings highlight the efficacy of combination therapy (Ins+SZ-A or Ins+Met) in improving blood glucose fluctuations, as well as blood glucose and lipid levels. Ins+SZ-A reduces postprandial blood glucose fluctuations more than Ins+Met and Ins groups. Trial registration number: ISRCTN20835488.

Deep learning-based aberration compensation improves contrast and resolution in fluorescence microscopy.

Optical aberrations hinder fluorescence microscopy of thick samples, reducing image signal, contrast, and resolution. Here we introduce a deep learning-based strategy for aberration compensation, improving image quality without slowing image acquisition, applying additional dose, or introducing more optics into the imaging path. Our method (i) introduces synthetic aberrations to images acquired on the shallow side of image stacks, making them resemble those acquired deeper into the volume and (ii) trains neural networks to reverse the effect of these aberrations. We use simulations to show that applying the trained 'de-aberration' networks outperforms alternative methods, and subsequently apply the networks to diverse datasets captured with confocal, light-sheet, multi-photon, and super-resolution microscopy. In all cases, the improved quality of the restored data facilitates qualitative image inspection and improves downstream image quantitation, including orientational analysis of blood vessels in mouse tissue and improved membrane and nuclear segmentation in C. elegans embryos.

Septins Enable T Cell Contact Guidance via Amoeboid-Mesenchymal Switch.

Lymphocytes exit circulation and enter in-tissue guided migration toward sites of tissue pathologies, damage, infection, or inflammation. By continuously sensing and adapting to the guiding chemo-mechano-structural properties of the tissues, lymphocytes dynamically alternate and combine their amoeboid (non-adhesive) and mesenchymal (adhesive) migration modes. However, which mechanisms guide and balance different migration modes are largely unclear. Here we report that suppression of septins GTPase activity induces an abrupt amoeboid-to-mesenchymal transition of T cell migration mode, characterized by a distinct, highly deformable integrin-dependent immune cell contact guidance. Surprisingly, the T cell actomyosin cortex contractility becomes diminished, dispensable and antagonistic to mesenchymal-like migration mode. Instead, mesenchymal-like T cells rely on microtubule stabilization and their non-canonical dynein motor activity for high fidelity contact guidance. Our results establish septin's GTPase activity as an important on/off switch for integrin-dependent migration of T lymphocytes, enabling their dynein-driven fluid-like mesenchymal propulsion along the complex adhesion cues.

Dynein-Powered Cell Locomotion Guides Metastasis of Breast Cancer.

The principal cause of death in cancer patients is metastasis, which remains an unresolved problem. Conventionally, metastatic dissemination is linked to actomyosin-driven cell locomotion. However, the locomotion of cancer cells often does not strictly line up with the measured actomyosin forces. Here, a complementary mechanism of metastatic locomotion powered by dynein-generated forces is identified. These forces arise within a non-stretchable microtubule network and drive persistent contact guidance of migrating cancer cells along the biomimetic collagen fibers. It is also shown that the dynein-powered locomotion becomes indispensable during invasive 3D migration within a tissue-like luminal network formed by spatially confining granular hydrogel scaffolds (GHS) made up of microscale hydrogel particles (microgels). These results indicate that the complementary motricity mediated by dynein is always necessary and, in certain instances, sufficient for disseminating metastatic breast cancer cells. These findings advance the fundamental understanding of cell locomotion mechanisms and expand the spectrum of clinical targets against metastasis.