Rehabilitation Assessment System for Stroke Patients Based on Fusion-Type Optoelectronic Plethysmography Device and Multi-Modality Fusion Model: Design and Validation.

This study aimed to propose a portable and intelligent rehabilitation evaluation system for digital stroke-patient rehabilitation assessment. Specifically, the study designed and developed a fusion device capable of emitting red, green, and infrared lights simultaneously for photoplethysmography (PPG) acquisition. Leveraging the different penetration depths and tissue reflection characteristics of these light wavelengths, the device can provide richer and more comprehensive physiological information. Furthermore, a Multi-Channel Convolutional Neural Network-Long Short-Term Memory-Attention (MCNN-LSTM-Attention) evaluation model was developed. This model, constructed based on multiple convolutional channels, facilitates the feature extraction and fusion of collected multi-modality data. Additionally, it incorporated an attention mechanism module capable of dynamically adjusting the importance weights of input information, thereby enhancing the accuracy of rehabilitation assessment. To validate the effectiveness of the proposed system, sixteen volunteers were recruited for clinical data collection and validation, comprising eight stroke patients and eight healthy subjects. Experimental results demonstrated the system's promising performance metrics (accuracy: 0.9125, precision: 0.8980, recall: 0.8970, F1 score: 0.8949, and loss function: 0.1261). This rehabilitation evaluation system holds the potential for stroke diagnosis and identification, laying a solid foundation for wearable-based stroke risk assessment and stroke rehabilitation assistance.

Effectiveness of Intelligent Control Strategies in Robot-Assisted Rehabilitation-A Systematic Review.

This review aims to provide a systematic analysis of the literature focused on the use of intelligent control systems in robotics for physical rehabilitation, identifying trends in recent research and comparing the effectiveness of intelligence used in control, with the aim of determining important factors in robot-assisted rehabilitation and how intelligent controller design can improve them. Seven electronic research databases were searched for articles published in the years 2015 - 2022 with articles selected based on relevance to the subject area of intelligent control systems in rehabilitation robotics. It was found that the most common use of intelligent algorithms for control is improving traditional control strategies with optimization and learning techniques. Intelligent algorithms are also commonly used in sensor output mapping, model construction, and for various data learning purposes. Experimental results show that intelligent controllers consistently outperform non-intelligent controllers in terms of transparency, tracking accuracy, and adaptability. Active participation of the patients and lowered interaction forces are consistently mentioned as important factors in improving the rehabilitation outcome as well as the patient experience. However, there are limited examples of studies presenting experimental results with impaired participants suffering limited range of motion, so the effectiveness of therapy provided by these systems is often difficult to quantify. A lack of universal evaluation criteria also makes it difficult to compare control systems outside of articles which use their own comparison criteria.

Phosphorylation of Doc2 by EphB2 modulates Munc13-mediated SNARE complex assembly and neurotransmitter release.

At the synapse, presynaptic neurotransmitter release is tightly controlled by release machinery, involving the soluble N-ethylmaleimide-sensitive factor attachment protein receptor (SNARE) proteins and Munc13. The Ca2+ sensor Doc2 cooperates with Munc13 to regulate neurotransmitter release, but the underlying mechanisms remain unclear. In our study, we have characterized the binding mode between Doc2 and Munc13 and found that Doc2 originally occludes Munc13 to inhibit SNARE complex assembly. Moreover, our investigation unveiled that EphB2, a presynaptic adhesion molecule (SAM) with inherent tyrosine kinase functionality, exhibits the capacity to phosphorylate Doc2. This phosphorylation attenuates Doc2 block on Munc13 to promote SNARE complex assembly, which functionally induces spontaneous release and synaptic augmentation. Consistently, application of a Doc2 peptide that interrupts Doc2-Munc13 interplay impairs excitatory synaptic transmission and leads to dysfunction in spatial learning and memory. These data provide evidence that SAMs modulate neurotransmitter release by controlling SNARE complex assembly.

Chiral-induced synthesis of chiral covalent organic frameworks core-shell microspheres for HPLC enantioseparation.

Two chiral covalent organic frameworks (CCOFs) core-shell microspheres based on achiral organic precursors by chiral-induced synthesis strategy for HPLC enantioseparation are reported for the first time. Using n-hexane/isopropanol as mobile phase, various kinds of racemates were selected as analytes and separated on the CCOF-TpPa-1@SiO2 and CCOF-TpBD@SiO2-packed columns with a low column backpressure (3 ~ 9 bar). The fabricated two CCOFs@SiO2 chiral columns exhibited good separation performance towards various racemates with high column efficiency (e.g., 19,500 plates m-1 for (4-fluorophenyl)ethanol and 18,900 plates m-1 for 1-(4-chlorophenyl)ethanol) and good reproducibility. Some effects have been investigated such as the analyte mass and column temperature on the HPLC enantioseparation. Moreover, the chiral separation results of the CCOF-TpPa-1@SiO2 chiral column and the commercialized Chiralpak AD-H column show a good complementarity. This study demonstrates that the usage of chiral-induced synthesis strategy for preparing CCOFs core-shell microspheres as a novel stationary phase has a good application potential in HPLC.

Continuous Motion Intention Prediction Using sEMG for Upper-Limb Rehabilitation: A Systematic Review of Model-Based and Model-Free Approaches.

Upper limb functional impairments persisting after stroke significantly affect patients' quality of life. Precise adjustment of robotic assistance levels based on patients' motion intentions using sEMG signals is crucial for active rehabilitation. This paper systematically reviews studies on continuous prediction of upper limb single joints and multi-joint combinations motion intention using Model-Based (MB) and Model-Free (MF) approaches over the past decade, based on 186 relevant studies screened from six major electronic databases. The findings indicate ongoing challenges in terms of subject composition, algorithm robustness and generalization, and algorithm feasibility for practical applications. Moreover, it suggests integrating the strengths of both MB and MF approaches to improve existing algorithms. Therefore, future research should further explore personalized MB-MF combination methods incorporating deep learning, attention mechanisms, muscle synergy features, motor unit features, and closed-loop feedback to achieve precise, real-time, and long-duration prediction of multi-joint complex movements, while further refining the transfer learning strategy for rapid algorithm deployment across days and subjects. Overall, this review summarizes the current research status, significant findings, and challenges, aiming to inspire future research on predicting upper limb motion intentions based on sEMG.

I-OMP: an improved OMP algorithm for channel state identification in an underwater wireless optical communication scenario.

Underwater wireless optical communication (UWOC) has attracted considerable interest owing to its capability of high data rates and low latency. As a crucial component of UWOC, the transmission characteristics of an underwater channel directly impact the system's performance metrics. However, the existing channel models cannot exactly capture the underwater channel states, thus degrading the observability of channel states. This paper proposes a hybrid-field channel model containing both far-field and near-field path components, in which the signal-dependent shot noise (SDSN) is incorporated as well to accurately describe the underwater channel behavior. Then an improved orthogonal matching pursuit (I-OMP) algorithm that estimates the far-field and near-field path components independently with different transform matrices is developed to obtain the underwater channel state. The performance analyses show that I-OMP can improve the estimation accuracy of underwater channels by iteratively minimizing the mean square error (MSE) and utilizing two different transform matrices, demonstrating the advantage of the proposed I-OMP over the existing methods.

LPS priming-induced immune tolerance mitigates LPS-stimulated microglial activation and social avoidance behaviors in mice.

In this study, we investigated the regulatory mechanisms underlying the effects of LPS tolerance on the inflammatory homeostasis of immune cells. LPS priming-induced immune tolerance downregulated cyclooxygenase-2, and lowered the production of prostaglandin-E2 in microglial cells. In addition, LPS tolerance downregulated the expression of suppressor of cytokine signaling 3, and inducible nitric oxide synthase/nitric oxide; suppressed the LPS-mediated induction of tumor necrosis factor-α, interleukin (IL)-6, and IL-1; and reduced reactive oxygen species production in microglial cells. LPS stimulation increased the levels of the adaptive response-related proteins heme oxygenase-1 and superoxide dismutase 2, and the levels of heme oxygenase-1 (HO-1) enhanced after LPS priming. Systemic administration of low-dose LPS (0.5 mg/kg) to mice for 4 consecutive days attenuated high-dose LPS (5 mg/kg)-induced inflammatory response, microglial activation, and proinflammatory cytokine expression. Moreover, repeated exposure to low-dose LPS suppressed the recruitment of peripheral monocytes or macrophages to brain regions and downregulated the expression of proinflammatory cytokines. Notably, LPS-induced social avoidance behaviors in mice were mitigated by immune tolerance. In conclusion, immune tolerance may reduce proinflammatory cytokine expression and reactive oxygen species production. Our findings provide insights into the effects of endotoxin tolerance on innate immune cells and social behaviors.

Structure Responsible for the Superconducting State in La3Ni2O7 at High-Pressure and Low-Temperature Conditions.

Very recently, a new superconductor with Tc = 80 K has been reported in nickelate (La3Ni2O7) at around 15-40 GPa conditions (Nature, 621, 493, 2023), which is the second type of unconventional superconductor, besides cuprates, with Tc above liquid nitrogen temperature. However, the phase diagram plotted in this report was mostly based on the transport measurement under low-temperature and high-pressure conditions, and the assumed corresponding X-ray diffraction (XRD) results were carried out at room temperature. This encouraged us to carry out in situ high-pressure and low-temperature synchrotron XRD experiments to determine which phase is responsible for the high Tc state. In addition to the phase transition from the orthorhombic Amam structure to the orthorhombic Fmmm structure, a tetragonal phase with the space group of I4/mmm was discovered when the sample was compressed to around 19 GPa at 40 K where the superconductivity takes place in La3Ni2O7. The calculations based on this tetragonal structure reveal that the electronic states that approached the Fermi energy were mainly dominated by the eg orbitals (3dz2 and 3dx2-y2) of Ni atoms, which are located in the oxygen octahedral crystal field. The correlation between Tc and this structural evolution, especially Ni-O octahedra regularity and the in-plane Ni-O-Ni bonding angles, is analyzed. This work sheds new light to identify what is the most likely phase responsible for superconductivity in double-layered nickelate.

Growing attention on the toxicity of Chinese herbal medicine: a bibliometric analysis from 2013 to 2022.

Introduction: Despite the clinical value of Chinese herbal medicine (CHM), restricted comprehension of its toxicity limits the secure and efficacious application. Previous studies primarily focused on exploring specific toxicities within CHM, without providing an overview of CHM's toxicity. The absence of a quantitative assessment of focal points renders the future research trajectory ambiguous. Therefore, this study aimed to reveal research trends and areas of concern for the past decade. Methods: A cross-sectional study was conducted on publications related to CHM and toxicity over the past decade from Web of Science Core Collection database. The characteristics of the publication included publication year, journal, institution, funding, keywords, and citation counts were recorded. Co-occurrence analysis and trend topic analysis based on bibliometric analysis were conducted on keywords and citations. Results: A total of 3,225 publications were analyzed. Number of annal publications increased over the years, with the highest number observed in 2022 (n = 475). The Journal of Ethnopharmacology published the most publications (n = 425). The most frequently used toxicity classifications in keywords were hepatotoxicity (n = 119) or drug-induced liver injury (n = 48), and nephrotoxicity (n = 40). Co-occurrence analysis revealed relatively loose connections between CHM and toxicity, and their derivatives. Keywords emerging from trend topic analysis for the past 3 years (2019-2022) included ferroptosis, NLRP3 inflammasome, machine learning, network pharmacology, traditional uses, and pharmacology. Conclusion: Concerns about the toxicity of CHM have increased in the past decade. However, there remains insufficient studies that directly explore the intersection of CHM and toxicity. Hepatotoxicity and nephrotoxicity, as the most concerned toxicity classifications associated with CHM, warrant more in-depth investigations. Apoptosis was the most concerned toxicological mechanism. As a recent increase in attention, exploring the mechanisms of ferroptosis in nephrotoxicity and NLRP3 inflammasome in hepatotoxicity could provide valuable insights. Machine learning and network pharmacology are potential methods for future studies.

Numerical Study on Effect of Aggregate Moisture on Mixing Process.

During the concrete mixing process, the transition of aggregates from a dry to a moist state introduces a crucial dynamic that significantly influences particle interaction, consequently impacting mixing homogeneity. In this paper, based on the discrete element method, the effect of aggregate moisture on the mixing process of sand and stone was investigated. The interaction between dry particles was described by the Hertz-Mindlin model, while the interaction between wet particles was calculated by the linear cohesion model considering the liquid bridge force. Additionally, a functional relationship between the moisture content and the parameters of the linear cohesive contact model was established. The results show that the numerical method can be employed to simulate the mixing process. Notably, when the moisture content of pebbles ranges from 0% to 0.75% and that of sand ranges from 0% to 10.9%, the linear cohesion model is deemed suitable. The standard deviation of the mixing homogeneity of wet particles is lower than that of dry particles for short mixing time, indicating that a small amount of liquid enhances mixing homogeneity. However, moisture has no obvious effect on mixing homogeneity for a long mixing time. This nuanced understanding of the interplay between moisture, particle interactions, and mixing duration contributes valuable insights to optimize concrete mixing processes.

Sulfone-Functionalized Chichibabin's Hydrocarbons: Stable Diradicaloids with Symmetry Breaking Charge Transfer Contributing to NIR Emission beyond 900 nm.

While monoradical emitters have emerged as a new route toward efficient organic light-emitting diodes, the luminescence property of organic diradicaloids is still scarcely explored. Herein, by devising a novel radical-radical coupling-based synthetic approach, we report a new class of sulfone-functionalized Chichibabin's hydrocarbon derivatives, SD-1-3, featuring varied substituent patterns and moderate to high diradical characters of 0.44-0.70, as highly stable diradicaloids with rarely seen NIR emission beyond 900 nm. Via comprehensive experimental and theoretical investigations, we reveal that the optoelectronic and magnetic properties of these materials are significantly tuned by the variations of substitutions (H/CF3/OMe) on the molecular skeletons. More importantly, quantum chemical computations indicate that the embedding of sulfone groups has contributed to a breaking of their quasi-C2 symmetry of these diradicaloid molecules and results in an excited-state charge transfer character. Therefore, a remarkably deep NIR emissive wavelength of up to 998 nm, together with a large Stokes shift (∼386 nm), is achieved for the CF3-based SD-2 molecule in tetrahydrofuran. To the best of our knowledge, such a luminescent wavelength of SD-2 has represented the longest wavelengths among the currently reported organic fluorescent radicals. Overall, our work not only establishes a new synthetic approach toward stable Chichibabin's hydrocarbons but also paves the way for designing NIR emissive open-shell materials with both fundamental understanding and feasible control of their luminescent properties.

Fatty infiltration in the posterior muscles of the lower extremities as an MRI feature in antimitochondrial antibody-associated myopathy.

OBJECTIVE: Idiopathic inflammatory myopathy (IIM) with antimitochondrial M2 antibody (AMA-M2) has been associated with distinct clinical characteristics. In this study, we explore the magnetic resonance imaging (MRI) findings of the muscles of the lower extremities in AMA-M2-positive IIM to gain more insight. METHODS: MRI of 22 lower extremity muscles was retrospectively evaluated in 14 patients with AMA-M2-positive IIM and 37 age- and sex-matched patients with AMA-M2-negative IIM. Muscles with inflammatory edema and fatty infiltration were assessed according to the Stramare and Mercuri criteria. RESULTS: Patients with AMA-M2-positive IIM had significantly higher incidence of MRI involvement with fatty infiltration in five lower extremity muscles, namely the adductor magnus (AM) (13/14 VS 14/37, p < 0.001), semimembranosus (SM) (13/14 VS 17/37, p = 0.002), biceps femoris (BF) (12/14 VS 15/37, p = 0.004), soleus (13/14 VS 23/37, p = 0.041), and the medial head of the gastrocnemius (Gastroc M) (13/14 VS 17/37, p = 0.002) than patients with AMA-M2-negative IIM. Furthermore, the severity scores of fatty infiltrations of the above five muscles in AMA-M2-positive IIM were significantly higher than those in patients with AMA-M2-negative IIM (p < 0.001). CONCLUSIONS: Severe fatty infiltrations of the AM, SM, BF, soleus, and Gastroc M in the posterior muscles of the lower extremities are dominant MRI features in our patients with AMA-M2-positive IIM. This unique muscle MRI character may be a helpful indicator in clinical practice for patients with AMA-M2-positive IIM. Key Points • Striking involvement and prominent fatty infiltrations of five lower extremity muscles (adductor magnus, semimembranosus, biceps femoris, soleus, and the medial head of the gastrocnemius) are interesting MRI performances. • Severe fatty infiltrations in the posterior muscles of the lower extremities are dominant MRI features in AMA-M2-positive IIM. • This unique muscle MRI character may be very helpful for the diagnosis of the AMA-M2-positive IIM.

A Photoelectromagnetic 3D Metal-Organic Framework from Flexible Tetraarylethylene-Backboned Ligand and Dynamic Copper-Based Coordination Chemistry.

Porous frameworks that display dynamic responsiveness are of interest in the fields of smart materials, information technology, etc. In this work, a novel copper-based dynamic metal-organic framework [Cu3TTBPE6(H2O)2] (H4TTBPE = 1,1,2,2-tetrakis(4″-(1H-tetrazol-5-yl)-[1,1″-biphenyl]-4-yl)ethane), denoted as HNU-1, is reported which exhibits modulable photoelectromagnetic properties. Due to the synergetic effect of flexible tetraarylethylene-backboned ligands and diverse copper-tetrazole coordination chemistries, a complex 3D tunneling network is established in this MOF by the layer-by-layer staggered assembly of triplicate monolayers, showing a porosity of 59%. These features further make it possible to achieve dynamic transitions, in which the aggregate-state MOF can be transferred to different structural states by changing the chemical environment or upon heating while displaying sensitive responsiveness in terms of light absorption, photoluminescence, and magnetic properties.

Treatment Response Assessment in Multiple Myeloma: Histogram Analysis of Total Tumor Apparent Diffusion Coefficient based on Whole-body Diffusion-weighted MR Imaging.

BACKGROUND: The International Myeloma Working Group (IMWG) consensus criteria for response assessment in multiple myeloma (MM) has methodological limitations. Whole-body diffusion-weighted imaging (DWI) with apparent diffusion coefficient (ADC) histogram analysis may be complementary to response assessment of MM. PURPOSE: To explore the role of histogram analysis of the ADC based on the total tumor volume (ttADC) in response assessment in patients with newly diagnosed MM (NDMM). STUDY TYPE: Retrospective. POPULATION: Thirty-six patients with NDMM. FIELD STRENGTH/SEQUENCE: 3.0T/single-shot DWI echo planar imaging (EPI) sequence with an integrated slice-by-slice shimming (iShim) technique. ASSESSMENT: Baseline (median: 1 day before treatment) and post-treatment (median: five cycles of therapy) whole-body DWI were analyzed. A region of interest (ROI) containing lesions on every section of baseline image was drawn to derive the per-patient total tumor data. Post-treatment image analysis was based on the same ROI as the corresponding baseline. Histogram metrics were extracted from both ROIs. Patients were categorized into the very good partial response or better (VGPR+) group and the less than VGPR group per the IMWG response criteria for response assessment. Progression-free survival (PFS) was also calculated. STATISTICAL TESTS: Mann-Whitney test and Fisher's exact or Chi-squared tests, Receiver operating characteristic (ROC) analysis and DeLong test, Kaplan-Meier analysis and Cox proportional hazards model. A two-tailed P-value <0.05 was considered statistically significant. RESULTS: Thirty patients were categorized into the VGPR+ group and six into the less than VGPR group. The ttADC histogram changes between post-treatment and baseline metrics (ΔttADC) revealed significant differences in all percentile values between the VGPR+ and less than VGPR groups. For distinguishing VGPR+, ΔttADC_5th percentile had the largest area under the curve (AUC) (0.950, 95% CI 0.821-0.995). Patients with lower ΔttADC_5th percentile values (cutoff point, 188.193) showed significantly longer PFS (HR = 34.911, 95% CI 6.392-190.677). DATA CONCLUSION: ttADC histogram may facilitate response assessment in patients with NDMM. LEVEL OF EVIDENCE: 3 TECHNICAL EFFICACY: Stage 4.

NR0B1 suppresses ferroptosis through upregulation of NRF2/c-JUN-CBS signaling pathway in lung cancer cells.

Ferroptosis has demonstrated significant potential in treating radiochemotherapy-resistant cancers, but its efficacy can be affected by recently discovered ferroptosis suppressors. In this study, we discovered that NR0B1 protects against erastin- or RSL3-induced ferroptosis in lung cancer cells. Transcriptomic analysis revealed that NR0B1 significantly interfered with the expression of 12 ferroptosis-related genes, and the expression level of NR0B1 positively correlated with that of c-JUN, NRF2, and CBS. We further revealed that NR0B1 suppression of ferroptosis depended on the activities of c-JUN, NRF2, and CBS. NR0B1 directly promoted the expression of NRF2 and c-JUN and indirectly upregulated CBS expression through enhancing NRF2 and/or c-JUN transcription. Moreover, we showed that NR0B1 depletion restrained xenograft tumor growth and facilitated RSL3-induced ferroptosis in the tumors. In conclusion, our findings uncover that NR0B1 suppresses ferroptosis by activating the c-JUN/NRF2-CBS signaling pathway in lung cancer cells, providing new evidence for the involvement of NR0B1 in drug resistance during cancer therapy.

Jiedu Fuzheng decoction improves the proliferation, migration, invasion and EMT of non-small cell lung cancer via the Wnt/ß-catenin pathway.

OBJECTIVES: This study aimed to investigate the effect of Jiedu Fuzheng decoction (JFD) in non-small cell lung cancer (NSCLC) and its potential therapeutic mechanism. RESULTS: We prepared JFD-medicated serum from rats and treated NSCLC cells (A549 and NCI-H1650) with 0.5, 1, and 2 mg/mL JFD-medicated serum. CCK-8 and colony formation assays were used to detect cell proliferation. Transwell assays showed that JFD attenuated cell migration and invasion. JFD and SKL2001 (Wnt/ß-catenin activator) were simultaneously used to treat NSCLC cells to verify that JFD regulated the biological behavior of NSCLC via Wnt/ß-catenin signaling. It was found that 2 mg/mL JFD had the most significant effect on the activity of NSCLC cells. JFD attenuated proliferation and metastasis but increased the proportion of apoptotic cells. At the same time, JFD downregulated N-cadherin, vimentin and ß-catenin protein expression in cancer cells. SKL2001 could restore the improvement of JFD on proliferation, metastasis and apoptosis. CONCLUSION: This study confirmed that JFD suppressed the occurrence and development of NSCLC by regulating Wnt/ß-catenin signaling and provided a novel therapeutic scheme for NSCLC.

Simultaneous Hip Implant Segmentation and Gruen Landmarks Detection.

The assessment of implant status and complications of Total Hip Replacement (THR) relies mainly on the clinical evaluation of the X-ray images to analyse the implant and the surrounding rigid structures. Current clinical practise depends on the manual identification of important landmarks to define the implant boundary and to analyse many features in arthroplasty X-ray images, which is time-consuming and could be prone to human error. Semantic segmentation based on the Convolutional Neural Network (CNN) has demonstrated successful results in many medical segmentation tasks. However, these networks cannot define explicit properties that lead to inaccurate segmentation, especially with the limited size of image datasets. Our work integrates clinical knowledge with CNN to segment the implant and detect important features simultaneously. This is instrumental in the diagnosis of complications of arthroplasty, particularly for loose implant and implant-closed bone fractures, where the location of the fracture in relation to the implant must be accurately determined. In this work, we define the points of interest using Gruen zones that represent the interface of the implant with the surrounding bone to build a Statistical Shape Model (SSM). We propose a multitask CNN that combines regression of pose and shape parameters constructed from the SSM and semantic segmentation of the implant. This integrated approach has improved the estimation of implant shape, from 74% to 80% dice score, making segmentation realistic and allowing automatic detection of Gruen zones. To train and evaluate our method, we generated a dataset of annotated hip arthroplasty X-ray images that will be made available.

Calcineurin suppresses rat H9c2 cardiomyocyteprotective autophagy under chronic intermittent hypoxia by downregulating the AMPK pathway.

Calcineurin plays a key role in cardiovascular pathogenesis by exerting pro-apoptotic effects in cardiomyocytes. However, whether calcineurin can regulate cardiomyocyte autophagy under conditions of chronic intermittent hypoxia (CIH) remains unclear. Here, we showed that CIH induced calcineurin activity in H9c2 cells, which attenuated adenosine monophosphate-activated protein kinase (AMPK) signaling and inhibited autophagy. In H9c2 cells, autophagy levels, LC3 expression, and AMPK phosphorylation were significantly elevated under conditions of CIH within 3 days. However, after 5 days of CIH, these effects were reversed and calcineurin activity and apoptosis were significantly increased. The calcineurin inhibitor 17-Allyl-1,14-dihydroxy-12-[2-(4-hydroxy-3-methoxycyclohexyl) -1-methylvinyl]-23,25-dimethoxy-13,19,21,27-tetramethyl-11,28-dioxa-4-azatricyclo- [22.3.1.04,9]octacos-18- ene-2,3,10,16-tetrone (FK506) restored AMPK activation and LC3 expression and attenuated CIH-induced H9c2 cell apoptosis. In contrast, calcineurin overexpression significantly attenuated the increase in LC3 expression and enhanced H9c2 cell apoptosis under conditions of CIH. Calcineurin inhibition failed to induce autophagy or alleviate apoptosis in H9c2 cells expressing a kinase-dead K45R AMPK mutant. Autophagy inhibition abrogated the protective effects of FK506-mediated calcineurin inhibition. These results indicate that calcineurin suppresses adaptive autophagy during CIH by downregulating AMPK activation. Our findings reveal the underlying mechanism of calcineurin and autophagy regulation during H9c2 cell survival under conditions of CIH and may provide a new strategy for preventing CIH-induced cardiomyocyte damage.

Detecting latent topics and trends of digital twins in healthcare: A structural topic model-based systematic review.

Objective: Digital twins (DTs) have received widespread attention recently, providing new ideas and possibilities for future healthcare. This review aims to provide a quantitative review to analyze specific study contents, research focus, and trends of DT in healthcare. Simultaneously, this review intends to expand the connotation of "healthcare" into two directions, namely "Disease treatment" and "Health enhancement" to analyze the content within the "DT + healthcare" field thoroughly. Methods: A data mining method named Structure Topic Modeling (STM) was used as the analytical tool due to its topic analysis ability and versatility. Google Scholar, Web of Science, and China National Knowledge Infrastructure supplied the material papers in this review. Results: A total of 94 high-quality papers published between 2018 and 2022 were gathered and categorized into eight topics, collectively covering the transformative impact across a broader spectrum in healthcare. Three main findings have emerged: (1) papers published in healthcare predominantly concentrate on technology development (artificial intelligence, Internet of Things, etc.) and application scenarios(personalized, precise, and real-time health service); (2) the popularity of research topics is influenced by various factors, including policies, COVID-19, and emerging technologies; and (3) the preference for topics is diverse, with a general inclination toward the attribute of "Health enhancement." Conclusions: This review underscores the significance of real-time capability and accuracy in shaping the future of DT, where algorithms and data transmission methods assume central importance in achieving these goals. Moreover, technological advancements, such as omics and Metaverse, have opened up new possibilities for DT in healthcare. These findings contribute to the existing literature by offering quantitative insights and valuable guidance to keep researchers ahead of the curve.

Magnetic Bistability in an Organic Radical-Based Charge Transfer Cocrystal.

We report herein an organic charge transfer cocrystal complex, consisting of a stable radical TPVr and an electron acceptor TCNQF4, as a rare sort of all-organic-based magnetic bistable materials with a thermally activated magnetic hysteresis loop over the temperature range from 170 to 260 K. Detailed X-ray crystallographic studies and theoretical calculations revealed that while a π-associated radical anion dimer was formed upon an integer charge transfer process from TPVr to the TCNQF4 molecules within the cocrystal lattice, the resulting TCNQF4·- π-dimers were found to exhibit varied intradimer π-stacking distances and singly occupied molecular orbital overlaps at different temperatures, thus yielding two different singlet states with distinct singlet-triplet gaps above and below the loop, which eventually contributed to the thermally excited molecular magnetic bistability.