The neutrophil-to-lymphocyte ratio levels over time correlate to all-cause hospital mortality in sepsis.

Objective: This research aims to investigate the prognosis value using the time-weighted average neutrophil-to-lymphocyte ratio (TWA-NLR) for predicting all-cause hospital mortality among sepsis patients. Data were analyzed through the use of the eICU Collaborative Research Database (eICU-CRD 2.0) as well as Medical Information Mart for Intensive Care IV 2.2 (MIMIC-IV 2.2). Methods: Septic patients from both eICU-CRD 2.0 as well as MIMIC-IV 2.2 databases were included. The neutrophil-to-lymphocyte ratios (NLR) were available for analysis, utilizing complete blood counts obtained on days one, four, and seven following ICU admission. The TWA-NLR was computed at the end of the seven days, and patients were then stratified based on TWA-NLR thresholds. 90-day all-cause mortality during hospitalization was the primary objective, with 60-day all-cause hospital mortality as a secondary objective. The correlation between TWA-NLR and sepsis patients' primary outcome was analyzed using univariable and multivariable Cox proportional hazard regressions. A restricted cubic spline (RCS) analysis was conducted in an attempt to confirm this association further, and subgroup analyses were employed to evaluate the correlation across various comorbidity groups. Results: 3921 patients were included from the eICU-CRD 2.0, and the hospital mortality rate was 20.8 %. Both multivariable as well as univariable Cox proportional hazard regression analyses revealed that TWA-NLR was independently correlated with 90-day all-cause hospital mortality, yielding a hazard ratio (HR) of 1.02 (95 % CI 1.01-1.02, P-value<0.01) as well as 1.12 (95 % CI 1.01-1.15, P-value<0.01), respectively. The RCS analysis demonstrated a significant nonlinear relationship between TWA-NLR and 90-day all-cause hospital mortality risk. The study subjects were divided into higher (>10.5) and lower (≤10.5) TWA-NLR cohorts. A significantly decreased incidence of 90-day all-cause hospital mortality (HR = 0.56, 95 % CI 0.48-0.64, P-value<0.01) and longer median survival time (40 days vs 24 days, P-value<0.05) were observed in the lower TWA-NLR cohort. However, septic patients with chronic pulmonary (interaction of P-value = 0.009) or renal disease (interaction of P-value = 0.008) exhibited significant interactive associations between TWA-NLR and 90-day all-cause hospital mortality, suggesting the predictive power of TWA-NLR may be limited in these subgroups. The MIMIC-IV 2.2 was utilized as a validation cohort and exhibited a similar pattern. Conclusion: Our findings suggest that TWA-NLR is a powerful and independent prognostic indicator for 90-day all-cause hospital mortality among septic patients, and the TWA-NLR cutoff value may prove a useful method for identifying high-risk septic patients.

Alteration in early resting­state functional MRI activity in comatose survivors of cardiac arrest: a prospective cohort study.

BACKGROUND: This study aimed to explore the characteristics of abnormal regional resting-state functional magnetic resonance imaging (rs-fMRI) activity in comatose patients in the early period after cardiac arrest (CA), and to investigate their relationships with neurological outcomes. We also explored the correlations between jugular venous oxygen saturation (SjvO2) and rs-fMRI activity in resuscitated comatose patients. We also examined the relationship between the amplitude of the N20-baseline and the rs-fMRI activity within the intracranial conduction pathway of somatosensory evoked potentials (SSEPs). METHODS: Between January 2021 and January 2024, eligible post-resuscitated patients were screened to undergo fMRI examination. The amplitude of low-frequency fluctuation (ALFF), fractional ALFF (fALFF), and regional homogeneity (ReHo) of rs-fMRI blood oxygenation level-dependent (BOLD) signals were used to characterize regional neural activity. Neurological outcomes were evaluated using the Glasgow-Pittsburgh cerebral performance category (CPC) scale at 3 months after CA. RESULTS: In total, 20 healthy controls and 31 post-resuscitated patients were enrolled in this study. The rs-fMRI activity of resuscitated patients revealed complex changes, characterized by increased activity in some local brain regions and reduced activity in others compared to healthy controls (P < 0.05). However, the mean ALFF values of the whole brain were significantly greater in CA patients (P = 0.011). Among the clusters of abnormal rs-fMRI activity, the cluster values of ALFF in the left middle temporal gyrus and inferior temporal gyrus and the cluster values of ReHo in the right precentral gyrus, superior frontal gyrus and middle frontal gyrus were strongly correlated with the CPC score (P < 0.001). There was a strong correlation between the mean ALFF and SjvO2 in CA patients (r = 0.910, P < 0.001). The SSEP N20-baseline amplitudes in CA patients were negatively correlated with thalamic rs-fMRI activity (all P < 0.001). CONCLUSIONS: This study revealed that abnormal rs-fMRI BOLD signals in resuscitated patients showed complex changes, characterized by increased activity in some local brain regions and reduced activity in others. Abnormal BOLD signals were associated with neurological outcomes in resuscitated patients. The mean ALFF values of the whole brain were closely related to SjvO2 levels, and changes in the thalamic BOLD signals correlated with the N20-baseline amplitudes of SSEP responses. TRIAL REGISTRATION: NCT05966389 (Registered July 27, 2023).

Thin film ferroelectric photonic-electronic memory.

To reduce system complexity and bridge the interface between electronic and photonic circuits, there is a high demand for a non-volatile memory that can be accessed both electrically and optically. However, practical solutions are still lacking when considering the potential for large-scale complementary metal-oxide semiconductor compatible integration. Here, we present an experimental demonstration of a non-volatile photonic-electronic memory based on a 3-dimensional monolithic integrated ferroelectric-silicon ring resonator. We successfully demonstrate programming and erasing the memory using both electrical and optical methods, assisted by optical-to-electrical-to-optical conversion. The memory cell exhibits a high optical extinction ratio of 6.6 dB at a low working voltage of 5 V and an endurance of 4 × 104 cycles. Furthermore, the multi-level storage capability is analyzed in detail, revealing stable performance with a raw bit-error-rate smaller than 5.9 × 10-2. This ground-breaking work could be a key technology enabler for future hybrid electronic-photonic systems, targeting a wide range of applications such as photonic interconnect, high-speed data communication, and neuromorphic computing.

U-shaped correlation of lymphocyte count with all-cause hospital mortality in sepsis and septic shock patients: a MIMIC-IV and eICU-CRD database study.

BACKGROUND: In sepsis, the relationship between lymphocyte counts and patient outcomes is complex. Lymphocytopenia and lymphocytosis significantly influence survival, illustrating the dual functionality of lymphocytes in responding to infections. This study investigates this complex interaction, focusing on how variations in lymphocyte counts correlate with all-cause hospital mortality among sepsis patients. METHODS: This retrospective cohort study analyzed data from two extensive critical care databases: the Medical Information Mart for Intensive Care IV 2.0 (MIMIC-IV 2.0) from Beth Israel Deaconess Medical Center, Boston, Massachusetts, and the eICU Collaborative Research Database (eICU-CRD), which was Multi-center database from over 200 hospitals across the United States conducted by Philips eICU Research Institute. We included adult patients aged 18 years and older who met the Sepsis-3 criteria, characterized by documented or suspected infection and a Sequential Organ Failure Assessment (SOFA) score of 2 or higher. Sepsis patients were categorized into quartiles based on lymphocyte counts. The primary outcome was all-cause mortality in the hospital, with 90 and 60-day all-cause mortality as the secondary outcomes. Univariable and multivariable Cox proportional hazard regressions were utilized to assess lymphocyte counts' impact on hospital mortality. An adjusted restricted cubic spline (RCS) analysis was performed to elucidate this relationship further. Subgroup analyses were also conducted to explore the association across various comorbidity groups among sepsis and septic shock patients. RESULTS: Our study included 37,054 patients, with an observed in-hospital mortality rate of 16.6%. Univariable and multivariable Cox proportional hazard regression models showed that lymphocyte counts were independently associated with in-hospital mortality (HR = 1.04, P < 0.01; HR = 1.06, P < 0.01). RCS regression analysis revealed a U-shaped relationship between lymphocyte levels and hospital mortality risk in sepsis and septic shock patients (P for overall < 0.001, P for nonliner < 0.01; P for overall = 0.002, P for nonliner = 0.014). Subgroup analyses revealed that elevated lymphocyte counts correlated with increased hospital mortality among sepsis patients with liver disease and requiring renal replacement therapy (P for overall = 0.021, P for nonliner = 0.158; P for overall = 0.025, P for nonliner = 0.759). These findings suggest that lymphocytes may have enhanced prognostic value in specific subsets of critically ill sepsis patients. CONCLUSION: Our findings demonstrate that lymphocyte counts are a significant independent predictor of hospital mortality in sepsis and septic shock patients. We observed a U-shaped association between lymphocyte levels and mortality risk, indicating that high and low counts are linked to increased mortality. This result highlights the complex role of lymphocytes in sepsis outcomes and suggests the need for further investigation into the underlying mechanisms and potential therapeutic approaches. Integrating lymphocyte count assessment into risk stratification algorithms and clinical decision support tools could enhance the early identification of high-risk sepsis patients.

Mechanism research of non-coding RNA in immune checkpoint inhibitors therapy.

Immune checkpoint inhibitor (ICI) therapies for tumors of different systems have attained significant achievements and have changed the current situation of tumor treatment due to their therapeutic characteristics of high specificity and low side effects. The immune checkpoint Programmed death 1/Programmed cell death-Ligand 1 (PD-1/PD-L1) axis exerts a vital role in the immune escape of tumor cells. As a result, it has become a key target for tumor immunotherapy. Therefore, to perfect research into potential regulatory factors for the PD-1/PD-L1 axis, in order to understand and illustrate tumor ICI therapy mechanisms, is a significant goal. Moreover, ncRNA has been verified to regulate the PD-1/PD-L1 axis in the tumor immune microenvironment to regulate tumor genesis and development. ncRNAs can improve or decrease the efficacy of ICI therapy by modulating PD-L1 expression. This review aimed to investigate the mechanisms of action of ncRNA in regulating the PD-1/PD-L1 axis in ICI therapy, to provide more efficient immunotherapy for tumors of different systems.

Memantine Inhibits Calcium-Permeable AMPA Receptors.

Memantine is an US Food and Drug Administration (FDA) approved drug that selectively inhibits NMDA-subtype ionotropic glutamate receptors (NMDARs) for treatment of dementia and Alzheimer's. NMDARs enable calcium influx into neurons and are critical for normal brain function. However, increasing evidence shows that calcium influx in neurological diseases is augmented by calcium-permeable AMPA-subtype ionotropic glutamate receptors (AMPARs). Here, we demonstrate that these calcium-permeable AMPARs (CP-AMPARs) are inhibited by memantine. Electrophysiology unveils that memantine inhibition of CP-AMPARs is dependent on their calcium permeability and the presence of their neuronal auxiliary subunit transmembrane AMPAR regulatory proteins (TARPs). Through cryo-electron microscopy we elucidate that memantine blocks CP-AMPAR ion channels in a unique mechanism of action from NMDARs. Furthermore, we demonstrate that memantine reverses a gain of function AMPAR mutation found in a patient with a neurodevelopmental disorder and inhibits CP-AMPARs in nerve injury. Our findings alter the paradigm for the memantine mechanism of action and provide a blueprint for therapeutic approaches targeting CP-AMPARs.

Two-dimensional and high-order directional information modulations for secure communications based on programmable metasurface.

Conventional wireless communication schemes indiscriminately transmit information into the whole space and pose inherent security risks. Recently, directional information modulation (DIM) has attracted enormous attention as a promising technology. DIM generates correct constellation symbols in the desired directions and distorts them in undesired directions, thus ensuring the security of the transmitted information. Although several DIM schemes have been reported, they suffer from defects of bulkiness, energy consumption, high cost, and inability to support two-dimensional (2D) and high-order modulations. Here, we propose a DIM scheme based on a 2-bit programmable metasurface (PM) that overcomes these defects. A fast and efficient discrete optimization algorithm is developed to optimize the digital coding sequences, and the correct constellation symbols can be generated and transmitted in multi-directional beams. As a proof-of-concept, three sets of constellation diagrams (8 phase shift keying (PSK), 16 quadrature amplitude modulation (QAM), and 64QAM) are realized in the multi-channel modes. This work provides an important route of employing DIM for ensuring physical-layer security and serves as a stepping stone toward endogenous secure communications.

A landscape of methodology and implementation of adaptive designs in cancer clinical trials.

BACKGROUND: The use of adaptive designs in cancer trials has considerably increased worldwide in recent years, along with the release of various guidelines for their application. This systematic review aims to comprehensively summarize the key methodological and executive features of adaptive designs in cancer clinical trials. METHODS: A comprehensive search from PubMed, EMBASE, and the Cochrane Central Register of Controlled Trials was conducted to screen eligible clinical trials that employed adaptive designs and were conducted in cancer patients. The methodological and executive characteristics of adaptive designs were the main measurements extracted. Descriptive analyses, primarily consisting of frequency and percentage, were employed to analyzed and reported the data. RESULTS: A total of 180 cancer clinical trials with adaptive designs were identified. The first three most common type of adaptive design was the group sequential design (n=114, 63.3 %), adaptive dose-finding design (n=22, 12.2 %), and adaptive platform design (n=16, 8.9 %). The results showed that 4.4 % (n=8) of trials conducted post hoc modifications, and around 29.4 % (n=53) did not provide the methods for controlling type I errors. Among phase II or above trials, 79.9 % (112/140) applied the surrogate endpoint as the primary outcome in these trials. Importantly, 27.2 % (49/180) of trials did not report clear information on the independent data monitoring committee (iDMC), and 13.3 % (n=24) without clear information on interim analyses. Interim analyses suggested 34.4 % (62/180) of trials being stopped for futility, 10.6 % (n=19) for efficacy, and 2.2 % (n=4) for safety concerns in the early stage. CONCLUSIONS: This study emphasizes adaptive designs in cancer trials face significant challenges in their design or strict implementation according to protocol, which might significantly compromise the validity and integrity of trials. It is thus important for researchers, sponsors, and policymakers to actively oversee and guide their application.

Self-shedding MOF-nanocarriers modulated CdS/MoSe2 heterojunction activity through in-situ ion exchange: An enhanced split-type photoelectrochemical sensor for deoxynivalenol.

Deoxynivalenol (DON), a mycotoxin produced by Fusarium, poses a significant risk to human health and the environment. Therefore, the development of a highly sensitive and accurate detection method is essential to monitor the pollution situation. In response to this imperative, we have devised an advanced split-type photoelectrochemical (PEC) sensor for DON analysis, which leverages self-shedding MOF-nanocarriers to modulate the photoelectric response ability of PEC substrate. The PEC sensing interface was constructed using CdS/MoSe2 heterostructures, while the self-shedding copper peroxide nanodots@ZIF-8 (CPNs@ZIF-8) served as the Cu2+ source for the in-situ ion exchange reaction, which generated a target-related signal reduction. The constructed PEC sensor exhibited a broad linear range of 0.1 pg mL-1 to 500 ng mL-1 with a low detection limit of 0.038 pg mL-1, demonstrating high stability, selectivity, and proactivity. This work not only introduces innovative ideas for the design of photosensitive materials, but also presents novel sensing strategies for detecting various environmental pollutants.

Calcineurin and CK2 Reciprocally Regulate Synaptic AMPA Receptor Phenotypes via α2δ-1 in Spinal Excitatory Neurons.

Calcineurin inhibitors, such as cyclosporine and tacrolimus (FK506), are commonly used immunosuppressants for preserving transplanted organs and tissues. However, these drugs can cause severe and persistent pain. GluA2-lacking, calcium-permeable AMPA receptors (CP-AMPARs) are implicated in various neurological disorders, including neuropathic pain. It is unclear whether and how constitutive calcineurin, a Ca2+/calmodulin protein phosphatase, controls synaptic CP-AMPARs. In this study, we found that blocking CP-AMPARs with IEM-1460 markedly reduced the amplitude of AMPAR-EPSCs in excitatory neurons expressing vesicular glutamate transporter-2 (VGluT2), but not in inhibitory neurons expressing vesicular GABA transporter, in the spinal cord of FK506-treated male and female mice. FK506 treatment also caused an inward rectification in the current-voltage relationship of AMPAR-EPSCs specifically in VGluT2 neurons. Intrathecal injection of IEM-1460 rapidly alleviated pain hypersensitivity in FK506-treated mice. Furthermore, FK506 treatment substantially increased physical interaction of α2δ-1 with GluA1 and GluA2 in the spinal cord and reduced GluA1/GluA2 heteromers in endoplasmic reticulum-enriched fractions of spinal cords. Correspondingly, inhibiting α2δ-1 with pregabalin, Cacna2d1 genetic knock-out, or disrupting α2δ-1-AMPAR interactions with an α2δ-1 C terminus peptide reversed inward rectification of AMPAR-EPSCs in spinal VGluT2 neurons caused by FK506 treatment. In addition, CK2 inhibition reversed FK506 treatment-induced pain hypersensitivity, α2δ-1 interactions with GluA1 and GluA2, and inward rectification of AMPAR-EPSCs in spinal VGluT2 neurons. Thus, the increased prevalence of synaptic CP-AMPARs in spinal excitatory neurons plays a major role in calcineurin inhibitor-induced pain hypersensitivity. Calcineurin and CK2 antagonistically regulate postsynaptic CP-AMPARs through α2δ-1-mediated GluA1/GluA2 heteromeric assembly in the spinal dorsal horn.

Vitamin D3 Regulates Energy Homeostasis under Short-Term Fasting Condition in Zebrafish (Danio Rerio).

Vitamin D3 (VD3) is a steroid hormone that plays pivotal roles in pathophysiology, and 1,25(OH)2D3 is the most active form of VD3. In the current study, the crucial role of VD3 in maintaining energy homeostasis under short-term fasting conditions was investigated. Our results confirmed that glucose-depriving pathways were inhibited while glucose-producing pathways were strengthened in zebrafish after fasting for 24 or 48 h. Moreover, VD3 anabolism in zebrafish was significantly suppressed in a time-dependent manner under short-fasting conditions. After fasting for 24 or 48 h, zebrafish fed with VD3 displayed a higher gluconeogenesis level and lower glycolysis level in the liver, and the serum glucose was maintained at higher levels, compared to those fed without VD3. Additionally, VD3 augmented the expression of fatty acids (FAs) transporter cd36 and lipogenesis in the liver, while enhancing lipolysis in the dorsal muscle. Similar results were obtained in cyp2r1-/- zebrafish, in which VD3 metabolism is obstructed. Importantly, it was observed that VD3 induced the production of gut GLP-1, which is considered to possess a potent gluconeogenic function in zebrafish. Meanwhile, the gene expression of proprotein convertase subtilisin/kexin type 1 (pcsk1), a GLP-1 processing enzyme, was also induced in the intestine of short-term fasted zebrafish. Notably, gut microbiota and its metabolite acetate were involved in VD3-regulated pcsk1 expression and GLP-1 production under short-term fasting conditions. In summary, our study demonstrated that VD3 regulated GLP-1 production in zebrafish by influencing gut microbiota and its metabolite, contributing to energy homeostasis and ameliorating hypoglycemia under short-term fasting conditions.

Calcineurin regulates synaptic Ca2+-permeable AMPA receptors in hypothalamic presympathetic neurons via α2δ-1-mediated GluA1/GluA2 assembly.

Hypertension is a major adverse effect of calcineurin inhibitors, such as tacrolimus (FK506) and cyclosporine, used clinically as immunosuppressants. Calcineurin inhibitor-induced hypertension (CIH) is linked to augmented sympathetic output from the hypothalamic paraventricular nucleus (PVN). GluA2-lacking, Ca2+-permeable AMPA receptors (CP-AMPARs) are a key feature of glutamatergic synaptic plasticity, yet their role in CIH remains elusive. Here, we found that systemic administration of FK506 in rats significantly increased serine phosphorylation of GluA1 and GluA2 in PVN synaptosomes. Strikingly, FK506 treatment reduced GluA1/GluA2 heteromers in both synaptosomes and endoplasmic reticulum-enriched fractions from the PVN. Blocking CP-AMPARs with IEM-1460 induced a larger reduction of AMPAR-mediated excitatory postsynaptic current (AMPAR-EPSC) amplitudes in retrogradely labelled, spinally projecting PVN neurons in FK506-treated rats than in vehicle-treated rats. Furthermore, FK506 treatment shifted the current-voltage relationship of AMPAR-EPSCs from linear to inward rectification in labelled PVN neurons. FK506 treatment profoundly enhanced physical interactions of α2δ-1 with GluA1 and GluA2 in the PVN. Inhibiting α2δ-1 with gabapentin, α2δ-1 genetic knockout, or disrupting α2δ-1-AMPAR interactions with an α2δ-1 C terminus peptide restored GluA1/GluA2 heteromers in the PVN and diminished inward rectification of AMPAR-EPSCs in labelled PVN neurons induced by FK506 treatment. Additionally, microinjection of IEM-1460 or α2δ-1 C terminus peptide into the PVN reduced renal sympathetic nerve discharges and arterial blood pressure elevated in FK506-treated rats but not in vehicle-treated rats. Thus, calcineurin in the hypothalamus constitutively regulates AMPAR subunit composition and phenotypes by controlling GluA1/GluA2 interactions with α2δ-1. Synaptic CP-AMPARs in PVN presympathetic neurons contribute to augmented sympathetic outflow in CIH. KEY POINTS: Systemic treatment with the calcineurin inhibitor increases serine phosphorylation of synaptic GluA1 and GluA2 in the PVN. Calcineurin inhibition enhances the prevalence of postsynaptic Ca2+-permeable AMPARs in PVN presympathetic neurons. Calcineurin inhibition potentiates α2δ-1 interactions with GluA1 and GluA2, disrupting intracellular assembly of GluA1/GluA2 heterotetramers in the PVN. Blocking Ca2+-permeable AMPARs or α2δ-1-AMPAR interactions in the PVN attenuates sympathetic outflow augmented by the calcineurin inhibitor.

Predicting sepsis in-hospital mortality with machine learning: a multi-center study using clinical and inflammatory biomarkers.

BACKGROUND: This study aimed to develop and validate an interpretable machine-learning model that utilizes clinical features and inflammatory biomarkers to predict the risk of in-hospital mortality in critically ill patients suffering from sepsis. METHODS: We enrolled all patients diagnosed with sepsis in the Medical Information Mart for Intensive Care IV (MIMIC-IV, v.2.0), eICU Collaborative Research Care (eICU-CRD 2.0), and the Amsterdam University Medical Centers databases (AmsterdamUMCdb 1.0.2). LASSO regression was employed for feature selection. Seven machine-learning methods were applied to develop prognostic models. The optimal model was chosen based on its accuracy, F1 score and area under curve (AUC) in the validation cohort. Moreover, we utilized the SHapley Additive exPlanations (SHAP) method to elucidate the effects of the features attributed to the model and analyze how individual features affect the model's output. Finally, Spearman correlation analysis examined the associations among continuous predictor variables. Restricted cubic splines (RCS) explored potential non-linear relationships between continuous risk factors and in-hospital mortality. RESULTS: 3535 patients with sepsis were eligible for participation in this study. The median age of the participants was 66 years (IQR, 55-77 years), and 56% were male. After selection, 12 of the 45 clinical parameters collected on the first day after ICU admission remained associated with prognosis and were used to develop machine-learning models. Among seven constructed models, the eXtreme Gradient Boosting (XGBoost) model achieved the best performance, with an AUC of 0.94 and an F1 score of 0.937 in the validation cohort. Feature importance analysis revealed that Age, AST, invasive ventilation treatment, and serum urea nitrogen (BUN) were the top four features of the XGBoost model with the most significant impact. Inflammatory biomarkers may have prognostic value. Furthermore, SHAP force analysis illustrated how the constructed model visualized the prediction of the model. CONCLUSIONS: This study demonstrated the potential of machine-learning approaches for early prediction of outcomes in patients with sepsis. The SHAP method could improve the interoperability of machine-learning models and help clinicians better understand the reasoning behind the outcome.

Macroscopic model and statistical model to characterize electromagnetic information of a digital coding metasurface.

A digital coding metasurface is a platform connecting the digital space and electromagnetic wave space, and has therefore gained much attention due to its intriguing value in reshaping wireless channels and realizing new communication architectures. Correspondingly, there is an urgent need for electromagnetic information theory that reveals the upper limit of communication capacity and supports the accurate design of metasurface-based communication systems. To this end, we propose a macroscopic model and a statistical model of the digital coding metasurface. The macroscopic model uniformly accommodates both digital and electromagnetic aspects of the meta-atoms and predicts all possible scattered fields of the digital coding metasurface based on a small number of simulations or measurements. Full-wave simulations and experimental results show that the macroscopic model is feasible and accurate. A statistical model is further proposed to correlate the mutual coupling between meta-atoms with covariance and to calculate the entropy of the equivalent currents of digital coding metasurface. These two models can help reconfigurable intelligent surfaces achieve more accurate beamforming and channel estimation, and thus improve signal power and coverage. Moreover, the models will encourage the creation of a precoding codebook in metasurface-based direct digital modulation systems, with the aim of approaching the upper limit of channel capacity. With these two models, the concepts of current space and current entropy, as well as the analysis of information loss from the coding space to wave space, is established for the first time, helping to bridge the gap between the digital world and the physical world, and advancing developments of electromagnetic information theory and new-architecture wireless systems.

Vitamin D promotes the folate transport and metabolism in zebrafish (Danio rerio).

Vitamin D (VD) is a fat-soluble sterol that possesses a wide range of physiological functions. The present study aimed to evaluate the effects of VD on folate metabolism in zebrafish and further investigated the underlying mechanism. Wild-type (WT) zebrafish were fed with a diet containing 0 IU/kg VD3 or 800 IU/kg VD3 for 3 wk. Meanwhile, cyp2r1 mutant zebrafish with impaired VD metabolism was used as another model of VD deficiency. Our results showed that VD deficiency in zebrafish suppressed the gene expression of folate transporters, including reduced folate carrier (RFC) and proton-coupled folate transporter (PCFT) in the intestine. Moreover, VD influenced the gene expression of several enzymes related to cellular folate metabolism in the intestine and liver of zebrafish. Importantly, VD-deficient zebrafish contained a remarkably lower level of folate content in the liver. Notably, VD was incapable of altering folate metabolism in zebrafish when gut microbiota was depleted by antibiotic treatment. Further studies proved that gut commensals from VD-deficient fish displayed a lower capacity to produce folate than those from WT fish. Our study revealed the potential correlation between VD and folate metabolism in zebrafish, and gut microbiota played a key role in VD-regulated folate metabolism in zebrafish.NEW & NOTEWORTHY Our study has identified that VD influences intestinal uptake and transport of folate in zebrafish while also altering hepatic folate metabolism and storage. Interestingly, the regulatory effects of VD on folate transport and metabolism diminished after the gut flora was interrupted by antibiotic treatment, suggesting that the regulatory effects of VD on folate metabolism in zebrafish are most likely dependent on the intestinal flora.

Detecting and Grounding Multi-Modal Media Manipulation and Beyond.

Misinformation has become a pressing issue. Fake media, in both visual and textual forms, is widespread on the web. While various DeepFake detection and text fake news detection methods have been proposed, they are only designed for single-modality forgery based on binary classification, let alone analyzing and reasoning subtle forgery traces across different modalities. In this paper, we highlight a new research problem for multi-modal fake media, namely Detecting and Grounding Multi-Modal Media Manipulation (DGM 4). DGM 4 aims to not only detect the authenticity of multi-modal media, but also ground the manipulated content (i.e., image bounding boxes and text tokens), which requires deeper reasoning of multi-modal media manipulation. To support a large-scale investigation, we construct the first DGM 4 dataset, where image-text pairs are manipulated by various approaches, with rich annotation of diverse manipulations. Moreover, we propose a novel HierArchical Multi-modal Manipulation rEasoning tRansformer (HAMMER) to fully capture the fine-grained interaction between different modalities. HAMMER performs: 1) manipulation-aware contrastive learning between two uni-modal encoders as shallow manipulation reasoning and 2) modality-aware cross-attention by multi-modal aggregator as deep manipulation reasoning. Dedicated manipulation detection and grounding heads are integrated from shallow to deep levels based on the interacted multi-modal information. To exploit more fine-grained contrastive learning for cross-modal semantic alignment, we further integrate Manipulation-Aware Contrastive Loss with Local View and construct a more advanced model HAMMER++. Finally, we build an extensive benchmark and set up rigorous evaluation metrics for this new research problem. Comprehensive experiments demonstrate the superiority of HAMMER and HAMMER++; several valuable observations are also revealed to facilitate future research in multi-modal media manipulation.

DeepmdQCT: A multitask network with domain invariant features and comprehensive attention mechanism for quantitative computer tomography diagnosis of osteoporosis.

In the medical field, the application of machine learning technology in the automatic diagnosis and monitoring of osteoporosis often faces challenges related to domain adaptation in drug therapy research. The existing neural networks used for the diagnosis of osteoporosis may experience a decrease in model performance when applied to new data domains due to changes in radiation dose and equipment. To address this issue, in this study, we propose a new method for multi domain diagnostic and quantitative computed tomography (QCT) images, called DeepmdQCT. This method adopts a domain invariant feature strategy and integrates a comprehensive attention mechanism to guide the fusion of global and local features, effectively improving the diagnostic performance of multi domain CT images. We conducted experimental evaluations on a self-created OQCT dataset, and the results showed that for dose domain images, the average accuracy reached 91%, while for device domain images, the accuracy reached 90.5%. our method successfully estimated bone density values, with a fit of 0.95 to the gold standard. Our method not only achieved high accuracy in CT images in the dose and equipment fields, but also successfully estimated key bone density values, which is crucial for evaluating the effectiveness of osteoporosis drug treatment. In addition, we validated the effectiveness of our architecture in feature extraction using three publicly available datasets. We also encourage the application of the DeepmdQCT method to a wider range of medical image analysis fields to improve the performance of multi-domain images.

Identification of a potential signature to predict the risk of postmenopausal osteoporosis.

BACKGROUND: Postmenopausal osteoporosis (PMOP) is related to the elevated risk of fracture in postmenopausal women. Thus, to effectively predict the occurrence of PMOP, we explored a novel gene signature for the prediction of PMOP risk. METHODS: The WGCNA analysis was conducted to identify the PMOP-related gene modules based on the data from GEO database (GSE56116 and GSE100609). The "limma" R package was applied for screening differentially expressed genes (DEGs) based on the data from GSE100609 dataset. Next, LASSO Cox algorithm were applied to identify valuable PMOP-related risk genes and construct a risk score model. GSEA was then conducted to analyze potential signaling pathways between high-risk (HR) score and low-risk (LR) score groups. RESULTS: A novel risk model with five PMOP-related risk genes (SCUBE3, TNNC1, SPON1, SEPT12 and ULBP1) was developed for predicting PMOP risk status. RT-qPCR and western blot assays validated that compared to postmenopausal non-osteoporosis (non-PMOP) patients, SCUBE3, ULBP1, SEPT12 levels were obviously elevated, and TNNC1 and SPON1 levels were reduced in blood samples from PMOP patients. Additionally, PMOP-related pathways such as MAPK signaling pathway, PI3K-Akt signaling pathway and HIF-1 signaling pathway were significantly activated in the HR-score group compared to the LR-score group. The circRNA-gene-miRNA and gene-transcription factor networks showed that 533 miRNAs, 13 circRNAs and 40 TFs might be involved in regulating the expression level of these five PMOP-related genes. CONCLUSION: Collectively, we developed a PMOP-related gene signature based on SCUBE3, TNNC1, SPON1, SEPT12 and ULBP1 genes, and higher risk score indicated higher risk suffering from PMOP.

H3K36 methyltransferase NSD1 protects against osteoarthritis through regulating chondrocyte differentiation and cartilage homeostasis.

Osteoarthritis (OA) is one of the most common joint diseases, there are no effective disease-modifying drugs, and the pathological mechanisms of OA need further investigation. Here, we show that H3K36 methylations were decreased in senescent chondrocytes and age-related osteoarthritic cartilage. Prrx1-Cre inducible H3.3K36M transgenic mice showed articular cartilage destruction and osteophyte formation. Conditional knockout Nsd1Prrx1-Cre mice, but not Nsd2Prrx1-Cre or Setd2Prrx1-Cre mice, replicated the phenotype of K36M/+; Prrx1-Cre mice. Immunostaining results showed decreased anabolic and increased catabolic activities in Nsd1Prrx1-Cre mice, along with decreased chondrogenic differentiation. Transcriptome and ChIP-seq data revealed that Osr2 was a key factor affected by Nsd1. Intra-articular delivery of Osr2 adenovirus effectively improved the homeostasis of articular cartilage in Nsd1Prrx1-Cre mice. In human osteoarthritic cartilages, both mRNA and protein levels of NSD1 and OSR2 were decreased. Our results indicate that NSD1-induced H3K36 methylations and OSR2 expression play important roles in articular cartilage homeostasis and OA. Targeting H3K36 methylation and OSR2 would be a novel strategy for OA treatment.

Constitutive KCC2 Cell- and Synapse-Specifically Regulates NMDA Receptor Activity in the Spinal Cord.

K+-Cl- cotransporter-2 (KCC2) critically controls neuronal chloride homeostasis and maintains normal synaptic inhibition by GABA and glycine. Nerve injury diminishes synaptic inhibition in the spinal cord via KCC2 impairment. However, how KCC2 regulates nociceptive input to spinal excitatory and inhibitory neurons remains elusive. Here, we show that basal GABA reversal potentials were significantly more depolarized in vesicular GABA transporter (VGAT)-expressing inhibitory neurons than those in vesicular glutamate transporter-2 (VGluT2)-expressing excitatory neurons in spinal cords of male and female mice. Strikingly, inhibiting KCC2 with VU0463271 increased currents elicited by puff NMDA and the NMDAR-mediated frequency of mEPSCs in VGluT2, but not in VGAT, dorsal horn neurons. Notably, VU0463271 had no effect on EPSCs monosynaptically evoked from the dorsal root in VGluT2 neurons. Furthermore, VU0463271 augmented α2δ-1-NMDAR interactions and their protein levels in spinal cord synaptosomes. In Cacna2d1 KO mice, VU0463271 had no effect on puff NMDA currents or the mEPSC frequency in dorsal horn neurons. Disrupting α2δ-1-NMDAR interactions with α2δ-1 C-terminus mimicking peptide diminished VU0463271-induced potentiation in the mEPSC frequency and puff NMDA currents in VGluT2 neurons. Additionally, intrathecal injection of VU0463271 reduced mechanical and thermal thresholds in wild-type mice, but not in Cacna2d1 KO mice. VU0463271-induced pain hypersensitivity in mice was abrogated by co-treatment with the NMDAR antagonist, pregabalin (an α2δ-1 inhibitory ligand), or α2δ-1 C-terminus mimicking peptide. Our findings suggest that KCC2 controls presynaptic and postsynaptic NMDAR activity specifically in excitatory dorsal horn neurons. KCC2 impairment preferentially potentiates nociceptive transmission between spinal excitatory interneurons via α2δ-1-bound NMDARs.Significance statementImpaired function of potassium-chloride cotransporter-2 (KCC2), a key regulator of neuronal inhibition, in the spinal cord plays a major role in neuropathic pain. This study unveils that KCC2 controls spinal nociceptive synaptic strength via NMDA receptors in a cell type- and synapse type-specific manner. KCC2 inhibition preferentially augments presynaptic and postsynaptic NMDA receptor activity in spinal excitatory interneurons via α2δ-1 (previously known as a calcium channel subunit). Importantly, spinal KCC2 impairment triggers pain hypersensitivity through α2δ-1-coupled NMDA receptors. These findings pinpoint the cell and molecular substrates for the reciprocal relationship between spinal synaptic inhibition and excitation in chronic neuropathic pain. Targeting both KCC2 and α2δ-1­NMDA receptor complexes could be an effective strategy in managing neuropathic pain conditions.