A linearized modeling framework for the frequency selectivity in neurons postsynaptic to vibration receptors.

Vibration is an indispensable part of the tactile perception, which is encoded to oscillatory synaptic currents by receptors and transferred to neurons in the brain. The A2 and B1 neurons in the drosophila brain postsynaptic to the vibration receptors exhibit selective preferences for oscillatory synaptic currents with different frequencies, which is caused by the specific voltage-gated Na+ and K+ currents that both oppose the variations in membrane potential. To understand the peculiar role of the Na+ and K+ currents in shaping the filtering property of A2 and B1 neurons, we develop a linearized modeling framework that allows to systematically change the activation properties of these ionic channels. A data-driven conductance-based biophysical model is used to reproduce the frequency filtering of oscillatory synaptic inputs. Then, this data-driven model is linearized at the resting potential and its frequency response is calculated based on the transfer function, which is described by the magnitude-frequency curve. When we regulate the activation properties of the Na+ and K+ channels by changing the biophysical parameters, the dominant pole of the transfer function is found to be highly correlated with the fluctuation of the active current, which represents the strength of suppression of slow voltage variation. Meanwhile, the dominant pole also shapes the magnitude-frequency curve and further qualitatively determines the filtering property of the model. The transfer function provides a parsimonious description of how the biophysical parameters in Na+ and K+ channels change the inhibition of slow variations in membrane potential by Na+ and K+ currents, and further illustrates the relationship between the filtering properties and the activation properties of Na+ and K+ channels. This computational framework with the data-driven conductance-based biophysical model and its linearized model contributes to understanding the transmission and filtering of vibration stimulus in the tactile system.

Prediction of hippocampal electric field in time series induced by TI-DMS with temporal convolutional network.

Temporal interference deep-brain magnetic stimulation (TI-DMS) induces rhythmic electric field (EF) in the hippocampus to normalize cognitive function. The rhythmic time series of the hippocampal EF is essential for the assessment of TI-DMS. However, the finite element method (FEM) takes several hours to obtain the time series of EF. In order to reduce the time cost, the temporal convolutional network (TCN) model is adopted to predict the time series of hippocampal EF induced by TI-DMS. It takes coil configuration and loaded current as input and predicts the time series of maximum and mean values of the left and right hippocampal EF. The prediction takes only a few seconds. The model parameter combination of kernel size and layers is selected optimally by cross-validation method. The experimental results for multiple subjects show that the R2 of all the time series predicted by the model exceed 0.98. And the prediction accuracy is even higher as the input parameters approach the training set. These results demonstrate that the adopted model can quickly predict the time series of hippocampal EF induced by TI-DMS with relatively high accuracy, which is beneficial for future clinical applications.

Protective Effects of Berberine on Nonalcoholic Fatty Liver Disease in db/db Mice via AMPK/SIRT1 Pathway Activation.

OBJECTIVE: Berberine (BBR) has emerged as a promising therapeutic agent for nonalcoholic fatty liver disease (NAFLD). This study aims to elucidate the underlying molecular mechanisms. METHODS: In this study, db/db mice were chosen as an animal model for NAFLD. A total of 10 healthy C57BL/6J mice and 30 db/db mice were randomly allocated to one of 4 groups: the normal control (NC) group, the diabetic control (DC) group, the Metformin (MET) therapy group, and the BBR therapy group. The total cholesterol (TC), triacylglycerol (TG), low-density lipoprotein cholesterol (LDL-c), high-density lipoprotein cholesterol (HDL-c), aspartate aminotransferase (AST) and alanine aminotransferase (ALT) levels in the serum were measured. The glutathione peroxidase (GSH-Px), glutathione (GSH), malondialdehyde (MDA), superoxide dismutase (SOD), catalase (CAT), interleukin (IL)-1ß, tumor necrosis factor (TNF)-α and monocyte chemotactic protein 1 (MCP-1) levels in liver tissue were measured. Hematoxylin and eosin (H&E), acid-Schiff (PAS) and TUNEL stanning was performed for histopathological analysis. Western blotting and immunohistochemistry were conducted to detect the expression levels of key proteins in the AMPK/SIRT1 pathway. RESULTS: BBR could improve lipid metabolism, attenuate hepatic steatosis and alleviate liver injury significantly. The excessive oxidative stress, high levels of inflammation and abnormal apoptosis in db/db mice were reversed after BBR intervention. BBR clearly changed the expression of AMP-activated protein kinase (AMPK)/Sirtuin 1 (SIRT1), and their downstream proteins. CONCLUSION: BBR could reverse NAFLD-related liver injury, likely by activating the AMPK/SIRT1 signaling pathway to inhibit oxidative stress, inflammation and apoptosis in hepatic tissue.

Tobacco as bioenergy and medical plant for biofuels and bioproduction.

Tobacco, a widely cultivated crop, has been extensively utilized by humans for an extended period. However, the tobacco industry generates a significant amount of organic waste, and the effective utilization of this tobacco waste has been limited. Currently, most tobacco waste is either recycled as reconstituted tobacco sheets or disposed of in landfills. However, tobacco possesses far more potential value than just these applications. This article provides an overview of the diverse uses of tobacco waste in agriculture, medicine, chemical engineering, and energy sectors. In the realm of agriculture, tobacco waste finds primary application as fertilizers and pesticides. In medical applications, the bioactive compounds present in tobacco are fully harnessed, resulting in the production of phenols, solanesol, polysaccharides, proteins, and even alkaloids. These bioactive compounds exhibit beneficial effects on human health. Additionally, the applications of tobacco waste in chemical engineering and energy sectors are centered around the utilization of lignocellulosic compounds and certain fuels. Chemical platform compounds derived from tobacco waste, as well as selected fuel sources, play a significant role in these areas. The rational utilization of tobacco waste represents a promising prospect, particularly in the present era when sustainable development is widely advocated. Moreover, this approach holds significant importance for enhancing energy utilization.

Non-classical Deactivation Mechanism in a Supported Intermetallic Catalyst for Propane Dehydrogenation.

Platinum-based supported intermetallic alloys (IMAs) demonstrate exceptional performance in catalytic propane dehydrogenation (PDH) primarily because of their remarkable resistance to coke formation. However, these IMAs still encounter a significant hurdle in the form of catalyst deactivation. Understanding the complex deactivation mechanism of supported IMAs, which goes beyond conventional coke deposition, requires meticulous microscopic structural elucidation. In this study, we unravel a nonclassical deactivation mechanism over a PtZn/γ-Al2O3 PDH catalyst, dictated by the PtZn to Pt3Zn nanophase transformation accompanied with dezincification. The physical origin lies in the metal support interaction (MSI) that enables strong chemical bonding between hydroxyl groups on the support and Zn sites on the PtZn phase to selectively remove Zn species followed by the reconstruction towards Pt3Zn phase. Building on these insights, we have devised a solution to circumvent the deactivation by passivating the MSI through surface modification of γ-Al2O3 support. By exchanging protons of hydroxyl groups with potassium ions (K) on the γ-Al2O3 support, such a strategy significantly minimizes the dezincification of PtZn IMA via diminished metal-support bonding, which dramatically reduces the deactivation rate from 0.2044 to 0.0587 h-1.

Molecular exploration of the diurnal alteration of glycogen structural fragility and stability in time-restricted-feeding mouse liver.

The structure of glycogen α particles in healthy mouse liver has two states: stability and fragility. In contrast, glycogen α particles in diabetic liver present consistent fragility, which may exacerbate hyperglycemia. Currently, the molecular mechanism behind glycogen structural alteration is still unclear. In this study, we characterized the fine molecular structure of liver glycogen α particles in healthy mice under time-restricted feeding (TRF) mode during a 24-h cycle. Then, differentially expressed genes (DEGs) in the liver during daytime and nighttime were revealed via transcriptomics, which identified that the key downregulated DEGs were mainly related to insulin secretion in daytime. Furthermore, GO annotation and KEGG pathway enrichment found that negative regulation of the glycogen catabolic process and insulin secretion process were significantly downregulated in the daytime. Therefore, transcriptomic analyses indicated that the structural stability of glycogen α particles might be correlated with the glycogen degradation process via insulin secretion downregulation. Further molecular experiments confirmed the significant upregulation of glycogen phosphorylase (PYGL), phosphorylated PYGL (p-PYGL), and glycogen debranching enzyme (AGL) at the protein level during the daytime. Overall, we concluded that the downregulation of insulin secretion in the daytime under TRF mode facilitated glycogenolysis, contributing to the structural stability of glycogen α-particles.

SERS detection platform based on a nucleic acid aptamer-functionalized Au nano-dodecahedron array for efficient simultaneous testing of colorectal cancer-associated microRNAs.

A surface-enhanced Raman scattering (SERS) detection platform was constructed based on Au nano-dodecahedrons (AuNDs) functionalized with nucleic acid aptamer-specific binding and self-assembly techniques. SERS labels were prepared by modifying Raman signaling molecules and complementary aptamer chains and were bound on the aptamer-functionalized AuNDs array. Using this protocol, the limits of detection (LODs) of miR-21 and miR-18a in the serum were 6.8 pM and 7.6 pM, respectively, and the detection time was 5 min. Additionally, miR-21 and miR-18a were detected in the serum of a mouse model of colorectal cancer. The results of this protocol were consistent with quantitative real-time polymerase chain reaction (qRT-PCR). This method provides an efficient and rapid method for the simultaneous testing of miRNAs, which has great potential clinical value for the early detection of colorectal cancer (CRC).

Exploring the nexus of smart technologies and sustainable ecotourism: A systematic review.

Sustainable smart ecotourism, utilizing smart technologies like smartphones, artificial intelligence (AI), and the Internet of Things (IoT), aims to minimize harm to natural and cultural ecosystems, promoting education and environmental conservation. This review aims to examine the concept of sustainable smart ecotourism, analyzing existing literature to gain insights into the significance, components, challenges, and contributions to sustainable development on a global scale. A systematic review was conducted to evaluate sustainable smart ecotourism using PRISMA guidelines. The review focused on scholarly, peer-reviewed studies from developing countries, using databases like ScienceDirect, Jstor, Taylor & Francis, and IEEE. The study used Joanna Briggs Institute and Cochrane Risk of Bias tools to assess study quality. Thematic analysis techniques were used to extract and synthesize data, identifying patterns and trends relevant to smart ecotourism sustainability. Dual analyst verification ensured data integrity and reliability. After conducting a thorough quality evaluation using the Joanna Briggs Institute Checklist and Cochrane Risk of Bias Tool, we identified 29 studies of exceptional quality from an original pool of 9583 records. The use of thematic analysis sheds light on the diverse and important role of the IoT in promoting sustainable ecotourism. This study uncovered both the obstacles and possibilities associated with this technology. The findings provide important insights into the worldwide implementation of smart ecotourism techniques and highlight the significant impact of technology in promoting sustainable tourism models. Smart ecotourism involves multiple stakeholders to enhance environmental impact. Key characteristics include dynamic interactions, co-creation of value, sustainable development, resource sharing, and innovation services. Technology like IoT is crucial for sustainable tourism management. Collaboration with governments, local stakeholders, and organizations is recommended for sustainable policies. As a result of this study, sustainable ecotourism policies result from a collaborative effort between local communities, government agencies, and practitioners in the industry. Smart technologies, including AR/VR and AI, have the potential to enhance operational efficiency while reducing environmental concerns. Ecotourism, partnerships, and education are key to successful implementation and capacity building.

Cross-sectional study on the epidemiological investigation ability of professional staff from Centers for Disease Control and Prevention in Guizhou Province.

Introduction: This study aims to evaluate the qualifications and identify skill enhancement areas for epidemiological investigators in Centers for Disease Control and Prevention (CDCs) in Guizhou's, informing future training and policy initiatives to strengthen public health responses. Methods: A cross-sectional survey was conducted in August 2022, and an online, self-designed questionnaire on the Epidemiological Dynamic Data Collection platform was administered to evaluate the professional staff in CDCs. The responses were scored and presented using descriptive statistical methods, and the factors influencing the total score were analyzed by one-way ANOVA and linear regression. Results and discussion: A total of 1321 questionnaires were collected, yielding an average score of 14.86±3.49 and a qualification rate of 29.9%. The scoring rate of ability of individual protection and coordination in epidemic control was high (87.25%). Meanwhile, improvements in further training were needed in areas such as data analysis ability (23.67%), knowledge of site disinfection (40.40%), and epidemiological investigation skills (42.50%). No significant difference was observed between the scores of city and county CDCs, (t = 1.071, p =0.284). The effects of gender and age could be disregarded, and the experience in epidemiological work and training (including investigation on COVID-19 cases and contacts), educational background, and professional title partially explained the survey outcome (R Square of the linear regression model was 0.351). The survey indicated the need for additional well-trained epidemiologic investigators in Guizhou. Specified training was effective in improving epidemiologic investigation, and enhancement in data analysis ability and knowledge of field disinfection are recommended in professional staff cultivation.

Individual Prediction of Electric Field Induced by Deep-Brain Magnetic Stimulation With CNN-Transformer.

Deep-brain Magnetic Stimulation (DMS) can improve the symptoms caused by Alzheimer's disease by inducing rhythmic electric field in the deep brain, and the induced electric field is rhythm-dependent. However, calculating the induced electric field requires building a voxel model of the brain for the stimulated object, which usually takes several hours. In order to obtain the rhythm-dependent electric field induced by DMS in real time, we adopt a CNN-Transformer model to predict it. A data set with a sample size of 7350 is established for the training and testing of the model. 10-fold cross validation is used to determine the optimal hyperparameters for training CNN-Transformer. The combination of 5-layer CNN and 6-layer Transformer is verified as the optimal combination of CNN-Transformer model. The experimental results show that the CNN-Transformer model can complete the prediction in 0.731s (CPU) or 0.042s (GPU), and the overall performance metrics of prediction can reach: MAE =0.0269, RMSE =0.0420, MAPE =4.61% and R2=0.9627. The prediction performance of the CNN-Transformer model for the hippocampal electric field is better than that of the brain grey matter electric field, and the stimulation rhythm has less influence on the model performance than the coil configuration. Taking the same dataset to train and test the separate CNN model and Transformer model, it is found that CNN-Transformer has better prediction performance than the separate CNN model and Transformer model in the task of predicting electric field induced by DMS.

Border cells without theta rhythmicity in the medial prefrontal cortex.

The medial prefrontal cortex (mPFC) is a key brain structure for higher cognitive functions such as decision-making and goal-directed behavior, many of which require awareness of spatial variables including one's current position within the surrounding environment. Although previous studies have reported spatially tuned activities in mPFC during memory-related trajectory, the spatial tuning of mPFC network during freely foraging behavior remains elusive. Here, we reveal geometric border or border-proximal representations from the neural activity of mPFC ensembles during naturally exploring behavior, with both allocentric and egocentric boundary responses. Unlike most of classical border cells in the medial entorhinal cortex (MEC) discharging along a single wall, a large majority of border cells in mPFC fire particularly along four walls. mPFC border cells generate new firing fields to external insert, and remain stable under darkness, across distinct shapes, and in novel environments. In contrast to hippocampal theta entrainment during spatial working memory tasks, mPFC border cells rarely exhibited theta rhythmicity during spontaneous locomotion behavior. These findings reveal spatially modulated activity in mPFC, supporting local computation for cognitive functions involving spatial context and contributing to a broad spatial tuning property of cortical circuits.

Sepiolite-Supported Manganese Oxide as an Efficient Catalyst for Formaldehyde Oxidation: Performance and Mechanism.

The current study involved the preparation of a number of MnOx/Sep catalysts using the impregnation (MnOx/Sep-I), hydrothermal (MnOx/Sep-H), and precipitation (MnOx/Sep-P) methods. The MnOx/Sep catalysts that were produced were examined for their ability to catalytically oxidize formaldehyde (HCHO). Through the use of several technologies, including N2 adsorption-desorption, XRD, FTIR, TEM, H2-TPR, O2-TPD, CO2-TPD, and XPS, the function of MnOx in HCHO elimination was examined. The MnOx/Sep-H combination was shown to have superior catalytic activities, outstanding cycle stability, and long-term activity. It was also able to perform complete HCHO conversion at 85 °C with a high GHSV of 6000 mL/(g·h) and 50% humidity. Large specific surface area and pore size, a widely dispersed active component, a high percentage of Mn3+ species, and lattice oxygen concentration all suggested a potential reaction route for HCHO oxidation. This research produced a low-cost, highly effective catalyst for HCHO purification in indoor or industrial air environments.

Functional hemodynamic imaging markers for the prediction of pathological outcomes in breast cancer patients treated with neoadjuvant chemotherapy.

Significance: Achieving pathologic complete response (pCR) after neoadjuvant chemotherapy (NACT) is a significant predictor of increased likelihood of survival in breast cancer patients. Early prediction of pCR is of high clinical value as it could allow personalized adjustment of treatment regimens in non-responding patients for improved outcomes. Aim: We aim to assess the association between hemoglobin-based functional imaging biomarkers derived from diffuse optical tomography (DOT) and the pathological outcome represented by pCR at different timepoints along the course of NACT. Approach: Twenty-two breast cancer patients undergoing NACT were enrolled in a multimodal DOT and X-ray digital breast tomosynthesis (DBT) imaging study in which their breasts were imaged at different compression levels. Logistic regressions were used to study the associations between DOT-derived imaging markers evaluated after the first and second cycles of chemotherapy, respectively, with pCR status determined after the conclusion of NACT at the time of surgery. Receiver operating characteristic curve analysis was also used to explore the predictive performance of selected DOT-derived markers. Results: Normalized tumor HbT under half compression was significantly lower in the pCR group compared to the non-pCR group after two chemotherapy cycles (p=0.042). In addition, the change in normalized tumor StO2 upon reducing compression from full to half mammographic force was identified as another potential indicator of pCR at an earlier time point, i.e., after the first chemo cycle (p=0.038). Exploratory predictive assessments showed that AUCs using DOT-derived functional imaging markers as predictors reach as high as 0.75 and 0.71, respectively, after the first and second chemo cycle, compared to AUCs of 0.50 and 0.53 using changes in tumor size measured on DBT and MRI. Conclusions: These findings suggest that breast DOT could be used to assist response assessment in women undergoing NACT, a critical but unmet clinical need, and potentially enable personalized adjustments of treatment regimens.

P2X7 receptor: a potential target for treating comorbid anxiety and depression.

In clinical practice, depression and anxiety frequently coexist, and they are both comorbid with somatic diseases. The P2X7R is an adenosine 5'-triphosphate (ATP)-gated non-selective cation channel that is widely expressed in immune-related cells. Under conditions of stress, chronic pain, and comorbid chronic physical illness, P2X7R activation in glial cells leads to neuroinflammation. This could contribute to the development of anxiety and depression-related emotional disturbances. Previous studies have shown that the P2X7 receptor (P2X7R) plays an important role in the pathogenesis of both anxiety and depression. Thus, the P2X7R may play a role in the comorbidity of anxiety and depression. Positron emission tomography can be used to assess the degree and location of neuroinflammation by monitoring functional and expression-related changes in P2X7R, which can facilitate clinical diagnoses and guide the treatment of patients with anxiety and depression. Moreover, single nucleotide polymorphisms (SNPs) in the P2X7R gene are associated with susceptibility to different types of psychiatric disorders. Thus, evaluating the SNPs of the P2X7R gene could enable personalized mood disorder diagnoses and treatments. If the P2X7R were set as a therapeutic target, selective P2X7R antagonists may modulate P2X7R function, thereby altering the balance of intra- and extra-cellular ATP. This could have therapeutic implications for treating anxiety and depression, as well as for pain management. According to in vitro and in vivo studies, the P2X7R plays an important role in anxiety and depression. In this review, we consider the potential of the P2X7R as a therapeutic target for comorbid anxiety and depression, and discuss the potential diagnostic and therapeutic value of this receptor.

Shared genetic basis and causality between schizophrenia and inflammatory bowel disease: evidence from a comprehensive genetic analysis.

BACKGROUND: The comorbidity between schizophrenia (SCZ) and inflammatory bowel disease (IBD) observed in epidemiological studies is partially attributed to genetic overlap, but the magnitude of shared genetic components and the causality relationship between them remains unclear. METHODS: By leveraging large-scale genome-wide association study (GWAS) summary statistics for SCZ, IBD, ulcerative colitis (UC), and Crohn's disease (CD), we conducted a comprehensive genetic pleiotropic analysis to uncover shared loci, genes, or biological processes between SCZ and each of IBD, UC, and CD, independently. Univariable and multivariable Mendelian randomization (MR) analyses were applied to assess the causality across these two disorders. RESULTS: SCZ genetically correlated with IBD (rg = 0.14, p = 3.65 × 10−9), UC (rg = 0.15, p = 4.88 × 10−8), and CD (rg = 0.12, p = 2.27 × 10−6), all surpassed the Bonferroni correction. Cross-trait meta-analysis identified 64, 52, and 66 significantly independent loci associated with SCZ and IBD, UC, and CD, respectively. Follow-up gene-based analysis found 11 novel pleiotropic genes (KAT5, RABEP1, ELP5, CSNK1G1, etc) in all joint phenotypes. Co-expression and pathway enrichment analysis illustrated those novel genes were mainly involved in core immune-related signal transduction and cerebral disorder-related pathways. In univariable MR, genetic predisposition to SCZ was associated with an increased risk of IBD (OR 1.11, 95% CI 1.07­1.15, p = 1.85 × 10−6). Multivariable MR indicated a causal effect of genetic liability to SCZ on IBD risk independent of Actinobacteria (OR 1.11, 95% CI 1.06­1.16, p = 1.34 × 10−6) or BMI (OR 1.11, 95% CI 1.04­1.18, p = 1.84 × 10−3). CONCLUSIONS: We confirmed a shared genetic basis, pleiotropic loci/genes, and causal relationship between SCZ and IBD, providing novel insights into the biological mechanism and therapeutic targets underlying these two disorders.

Pharmacokinetic Interactions Between Tegoprazan and the Combination of Clarithromycin, Amoxicillin and Bismuth in Healthy Chinese Subjects: An Open-Label, Single-Center, Multiple-Dosage, Self-Controlled, Phase I Trial.

BACKGROUND: Tegoprazan is a potassium-competitive acid blocker that inhibits gastric acid and which may be used for eradicating Helicobacter pylori. This study focuses on the pharmacokinetic interaction and safety between tegoprazan and the combination of clarithromycin, amoxicillin and bismuth in healthy Chinese subjects. METHODS: An open-label, three-period, single-center, multiple-dosage, single-sequence, phase I trial was conducted in 22 healthy subjects. In period 1, the subjects took tegoprazan 50 mg twice daily for 7 days, and in period 2 they were administered clarithromycin 500 mg, amoxicillin 1000 mg and bismuth potassium citrate 600 mg twice daily for 7 days (days 14-20). Tegoprazan, clarithromycin, amoxicillin and bismuth potassium citrate were then administered in combination for 7 days (days 21-27) in period 3. Blood samples were collected up to 12 h after the last dose of each period. Safety assessments were performed in each period. RESULTS: The geometric mean ratios (GMRs) [90% confidence interval (CI)] of maximum plasma concentration at steady state (Cmax,ss) and area under the plasma concentration-time curve over the dosing interval (AUCτ) at steady state were 195.93% (175.52-218.71%) and 287.54% (263.28-314.04%) for tegoprazan and 423.23% (382.57-468.22%) and 385.61% (354.62-419.30%) for tegoprazan metabolite M1, respectively. The GMRs (90% CI) of Cmax,ss and AUCτ were 83.69% (77.44-90.45%) and 110.30% (102.74-118.41%) for clarithromycin, 126.25% (114.73-138.93%) and 146.94% (135.33-159.55%) for 14-hydroxyclarithromycin, 75.89% (69.73-82.60%) and 94.34% (87.94-101.20%) for amoxicillin, and 158.43% (125.43-200.11%) and 183.63% (156.42-215.58%) for bismuth, respectively. All reported adverse events were mild. The frequency of adverse events during the coadministration stage was not higher than that during the single- or triple-drug administration stages. CONCLUSION: The plasma exposure of tegoprazan, M1, 14-hydroxyclarithromycin and bismuth was increased after the coadministration of tegoprazan, clarithromycin, amoxicillin and bismuth. The coadministration exhibited favorable safety and tolerability. CLINICAL TRIALS REGISTRATION: CTR20230643.

Bioinformatics and system biology approach to identify the influences among COVID-19, influenza, and HIV on the regulation of gene expression.

Background: Coronavirus disease (COVID-19), caused by SARS-CoV-2, has emerged as a infectious disease, coexisting with widespread seasonal and sporadic influenza epidemics globally. Individuals living with HIV, characterized by compromised immune systems, face an elevated risk of severe outcomes and increased mortality when affected by COVID-19. Despite this connection, the molecular intricacies linking COVID-19, influenza, and HIV remain unclear. Our research endeavors to elucidate the shared pathways and molecular markers in individuals with HIV concurrently infected with COVID-19 and influenza. Furthermore, we aim to identify potential medications that may prove beneficial in managing these three interconnected illnesses. Methods: Sequencing data for COVID-19 (GSE157103), influenza (GSE185576), and HIV (GSE195434) were retrieved from the GEO database. Commonly expressed differentially expressed genes (DEGs) were identified across the three datasets, followed by immune infiltration analysis and diagnostic ROC analysis on the DEGs. Functional enrichment analysis was performed using GO/KEGG and Gene Set Enrichment Analysis (GSEA). Hub genes were screened through a Protein-Protein Interaction networks (PPIs) analysis among DEGs. Analysis of miRNAs, transcription factors, drug chemicals, diseases, and RNA-binding proteins was conducted based on the identified hub genes. Finally, quantitative PCR (qPCR) expression verification was undertaken for selected hub genes. Results: The analysis of the three datasets revealed a total of 22 shared DEGs, with the majority exhibiting an area under the curve value exceeding 0.7. Functional enrichment analysis with GO/KEGG and GSEA primarily highlighted signaling pathways associated with ribosomes and tumors. The ten identified hub genes included IFI44L, IFI44, RSAD2, ISG15, IFIT3, OAS1, EIF2AK2, IFI27, OASL, and EPSTI1. Additionally, five crucial miRNAs (hsa-miR-8060, hsa-miR-6890-5p, hsa-miR-5003-3p, hsa-miR-6893-3p, and hsa-miR-6069), five essential transcription factors (CREB1, CEBPB, EGR1, EP300, and IRF1), and the top ten significant drug chemicals (estradiol, progesterone, tretinoin, calcitriol, fluorouracil, methotrexate, lipopolysaccharide, valproic acid, silicon dioxide, cyclosporine) were identified. Conclusion: This research provides valuable insights into shared molecular targets, signaling pathways, drug chemicals, and potential biomarkers for individuals facing the complex intersection of COVID-19, influenza, and HIV. These findings hold promise for enhancing the precision of diagnosis and treatment for individuals with HIV co-infected with COVID-19 and influenza.

A Low Systemic Inflammatory Response Index Is Associated With Improved Survival in Adenoid Cystic Carcinoma Patients.

BACKGROUND: Predicting the long-term survival in adenoid cystic carcinoma (ACC) patients remains challenging. Inflammatory cell-based indices are emerging as prognostic indicators of oncology. PURPOSE: This study aimed to determine the associations between the preoperative systemic inflammatory response index (SIRI) and the systemic immunoinflammatory index (SII) and the 10-year survival rates in patients with ACC of the head and neck (ACCHN). STUDY DESIGN, SETTING, SAMPLE: This retrospective cohort study comprised ACCHN patients treated at the Chinese People's Liberation Army General Hospital between November 2003 and December 2020. PREDICTOR VARIABLE: The inflammatory response, assessed using the SIRI and SII, was the predictor variable. The optimal cutoff values were based on the maximum Youden index values (sensitivity ＋ specificity－1). The patients were divided into two groups each, based on the SIRI (low, ≤ 0.15) and (high, > 0.15), and SII (low, ≤ 562.8 and high, > 562.8) values. MAIN OUTCOME VARIABLE(S): Overall survival (OS), or the number of days, weeks, or months between treatment initiation and death (or the last follow-up date), was the primary outcome variable. COVARIATES: The covariates were classified as demographic (age, gender, body mass index), medical (hypertension, diabetes), inflammatory (neutrophils, lymphocytes, monocytes, platelets, lymphocyte-monocyte ratio, platelet-lymphocyte ratio, neutrophil-lymphocyte ratio), and perioperative (tumor stage, lymph node metastasis, tumor size, treatment type). ANALYSES: Descriptive, univariate, and multivariate Cox proportional risk regression analyses were performed to determine whether the SIRI and SII were independent prognostic factors for OS. Kaplan-Meier survival curves and log-rank tests were used to determine their associations with the OS. RESULTS: The study sample comprised 162 patients (mean age, 52 ± 14; males, 39.5%). The median follow-up time was 6.81 ± 0.23, and the 10-year OS rate was 7.68 ± 0.25. The low and high SIRI groups comprised 109 and 53 patients, while the low and high SII groups comprised 116 and 46 patients, respectively. SIRI was identified as a prognostic factor (P < .01; hazard ratio, 2.45; 95% confidence interval, 1.35-4.45). CONCLUSION AND RELEVANCE: The SIRI has the advantages of reproducibility, convenience, noninvasiveness, and affordability, making it a promising prognostic inflammatory index for patients with ACCHN.