Enhancing emotion regulation: investigating the efficacy of transcutaneous electrical acupoint stimulation at PC6 in reducing fear of heights.

This study investigated the impact of transcutaneous electrical acupoint stimulation (TEAS) at Neiguan acupoint (PC6) on the physiological and behavioral responses of participants exposed in virtual height. 40 participants were included in the study and were randomly assigned to either a control group or an intervention group. Participants had an immersive experience with a VR interactive platform that provided somatosensory interaction in height stimulation scenes. Psychological scores, behavioral and cognitive performance, and physiological responses were recorded and analyzed. The results indicated that the intervention group had significantly lower fear scores compared to the control group. Analysis of heart rate variability revealed that the intervention group exhibited improved heart rate variability, indicating enhanced cardiovascular function and emotion regulation. The behavioral and cognitive results demonstrated that the intervention group exhibited higher left eye openness, faster reaction times, and greater movement distance, suggesting enhanced attentional focus, cognitive processing, and reduced avoidance behaviors. These findings suggest that TEAS at PC6 can effectively reduce fear and improve the regulation of physiological and behavioral responses to negative emotional stimuli.

Alternative polyadenylation regulates the translation of metabolic and inflammation-related proteins in adipose tissue of gestational diabetes mellitus.

In gestational diabetes mellitus (GDM), adipose tissue undergoes metabolic disturbances and chronic low-grade inflammation. Alternative polyadenylation (APA) is a post-transcriptional modification mechanism that generates mRNA with variable lengths of 3' untranslated regions (3'UTR), and it is associated with inflammation and metabolism. However, the role of APA in GDM adipose tissue has not been well characterized. In this study, we conducted transcriptomic and proteomic sequencing on subcutaneous and omental adipose tissues from both control and GDM patients. Using Dapars, a novel APA quantitative algorithm, we delineated the APA landscape of adipose tissue, revealing significant 3'UTR elongation of mRNAs in the GDM group. Omental adipose tissue exhibited a significant correlation between elongated 3'UTRs and reduced translation levels of genes related to metabolism and inflammation. Validation experiments in THP-1 derived macrophages (TDMs) demonstrated the impact of APA on translation levels by overexpressing long and short 3'UTR isoforms of a representative gene LRRC25. Additionally, LRRC25 was validated to suppress proinflammatory polarization in TDMs. Further exploration revealed two underexpressed APA trans-acting factors, CSTF3 and PPP1CB, in GDM omental adipose tissue. In conclusion, this study provides preliminary insights into the APA landscape of GDM adipose tissue. Reduced APA regulation in GDM omental adipose tissue may contribute to metabolic disorders and inflammation by downregulating gene translation levels. These findings advance our understanding of the molecular mechanisms underlying GDM-associated adipose tissue changes.

[Microwave Heartprint: A novel non-contact human identification technology based on cardiac micro-motion detection using ultra wideband bio-radar].

The existing one-time identity authentication technology cannot continuously guarantee the legitimacy of user identity during the whole human-computer interaction session, and often requires active cooperation of users, which seriously limits the availability. This study proposes a new non-contact identity recognition technology based on cardiac micro-motion detection using ultra wideband (UWB) bio-radar. After the multi-point micro-motion echoes in the range dimension of the human heart surface area were continuously detected by ultra wideband bio-radar, the two-dimensional principal component analysis (2D-PCA) was exploited to extract the compressed features of the two-dimensional image matrix, namely the distance channel-heart beat sampling point (DC-HBP) matrix, in each accurate segmented heart beat cycle for identity recognition. In the practical measurement experiment, based on the proposed multi-range-bin & 2D-PCA feature scheme along with two conventional reference feature schemes, three typical classifiers were selected as representatives to conduct the heart beat identification under two states of normal breathing and breath holding. The results showed that the multi-range-bin & 2D-PCA feature scheme proposed in this paper showed the best recognition effect. Compared with the optimal range-bin & overall heart beat feature scheme, our proposed scheme held an overall average recognition accuracy of 6.16% higher (normal respiration: 6.84%; breath holding: 5.48%). Compared with the multi-distance unit & whole heart beat feature scheme, the overall average accuracy increase was 27.42% (normal respiration: 28.63%; breath holding: 26.21%) for our proposed scheme. This study is expected to provide a new method of undisturbed, all-weather, non-contact and continuous identification for authentication.

Vision-driven metasurfaces for perception enhancement.

Metasurfaces have exhibited unprecedented degree of freedom in manipulating electromagnetic (EM) waves and thus provide fantastic front-end interfaces for smart systems. Here we show a framework for perception enhancement based on vision-driven metasurface. Human's eye movements are matched with microwave radiations to extend the humans' perception spectrum. By this means, our eyes can "sense" visual information and invisible microwave information. Several experimental demonstrations are given for specific implementations, including a physiological-signal-monitoring system, an "X-ray-glasses" system, a "glimpse-and-forget" tracking system and a speech reception system for deaf people. Both the simulation and experiment results verify evident advantages in perception enhancement effects and improving information acquisition efficiency. This framework can be readily integrated into healthcare systems to monitor physiological signals and to offer assistance for people with disabilities. This work provides an alternative framework for perception enhancement and may find wide applications in healthcare, wearable devices, search-and-rescue and others.

A Novel Non-Contact Detection and Identification Method for the Post-Disaster Compression State of Injured Individuals Using UWB Bio-Radar.

Building collapse leads to mechanical injury, which is the main cause of injury and death, with crush syndrome as its most common complication. During the post-disaster search and rescue phase, if rescue personnel hastily remove heavy objects covering the bodies of injured individuals and fail to provide targeted medical care, ischemia-reperfusion injury may be triggered, leading to rhabdomyolysis. This may result in disseminated intravascular coagulation or acute respiratory distress syndrome, further leading to multiple organ failure, which ultimately leads to shock and death. Using bio-radar to detect vital signs and identify compression states can effectively reduce casualties during the search for missing persons behind obstacles. A time-domain ultra-wideband (UWB) bio-radar was applied for the non-contact detection of human vital sign signals behind obstacles. An echo denoising algorithm based on PSO-VMD and permutation entropy was proposed to suppress environmental noise, along with a wounded compression state recognition network based on radar-life signals. Based on training and testing using over 3000 data sets from 10 subjects in different compression states, the proposed multiscale convolutional network achieved a 92.63% identification accuracy. This outperformed SVM and 1D-CNN models by 5.30% and 6.12%, respectively, improving the casualty rescue success and post-disaster precision.

Synoviolin alleviates GSDMD-mediated periodontitis by suppressing its stability.

INTRODUCTION: Inflammasome and pyroptosis play important roles in periodontitis. Gasdermin D (GSDMD), a key factor in pyroptosis, is cleaved by caspase-1 and regulated by ubiquitination. Synoviolin is a ubiquitin E3 ligase that interacts with GSDMD. In this study, the effects of Synoviolin on inflammasome activation and periodontitis were explored. METHODS: The expression of IL-1ß, GSDMD, and Synoviolin in peripheral blood mononuclear cells from patients with periodontitis was determined. The interaction between GSDMD and Synoviolin was studied. The cytokine level in gingival tissues and the distance from the cementoenamel junction to the alveolar bone crest were measured in mice with Synoviolin deficiency in myeloid cells. RESULTS: We reported that elevated mRNA and protein levels of IL-1ß and GSDMD, decreased levels of Synoviolin mRNA and protein, and decreased ubiquitination of GSDMD were associated with periodontitis. Synoviolin interacted with GSDMD. Synoviolin-deficient bone marrow-derived macrophages had increased IL-1ß and IL-18 secretion after ATP stimulation. Mice with Synoviolin deficiency in myeloid cells had more severe periodontitis and upregulated IL-1ß and IL-18. CONCLUSIONS: Therefore, we conclude that Synoviolin suppresses inflammasome activation and periodontitis by regulating GSDMD stability.

Cancer prediction from few amounts of histology samples through self-attention based multi-routines cross-domains network.

OBJECTIVE: Rapid and efficient analysis of cancer has become a focus of research. Artificial intelligence can use histopathological data to quickly determine the cancer situation, but still faces challenges. For example, the convolutional network is limited by the local receptive field, human histopathological information is precious and difficult to be collected in large quantities, and cross-domain data is hard to be used to learn histopathological features. In order to alleviate the above questions, we design a novel network, Self-attention based multi-routines cross-domains network (SMC-Net). APPROACH: Feature analysis module and decoupling analysis module designed are the core of the SMC-Net. The feature analysis module base on multi-subspace self-attention mechanism with pathological feature channel embedding. It in charge of learning the interdependence between pathological features to alleviate the problem that the classical convolution model is difficult to learn the impact of joint features on pathological examination results. The decoupling analysis module base on the designed multi-channel and multi-discriminator architecture. Its function is to decouple the features related to the target task in cross-domain samples so that the model has cross-domain learning ability. MAIN RESULTS: To evaluate the performance of the model more objectively, three datasets are used. Compared with other popular methods, our model achieves better performance without performance imbalance. In this work, a novel network is design. It can use domain-independent data to assist in the learning of target tasks, and can achieve acceptable histopathological diagnosis results even in the absence of data. SIGNIFICANCE: The proposed method has higher clinical embedding potential and provides a viewpoint for the combination of deep learning and histopathological examination.

Recombinant Irisin Protects Against Alveolar Bone Destruction During Orthodontic Tooth Movement.

Patients with periodontitis have higher risk of alveolar bone loss when seek for orthodontic therapy. Inflammation and osteogenesis are key factors in alveolar bone destruction in periodontitis and orthodontic tooth movement (OTM). Here we evaluated the effects of irisin on alveolar bone destruction in rats with periodontitis and OTM. We isolated and cultured human periodontal ligament stem cells (PDLSCs). Irisin was administrated to PDLSCs. Cell proliferations, osteogenic differentiation, expression of RUNX2 and ALP, and the expression of OPG and RANKL were measured. We induced periodontitis and OTM in rats and treated rats with irisin. The alveolar bone loss, inflammatory cytokine levels, and expression of OPG and RANKL in gingival tissues were measured. Irisin promoted the cell proliferation and osteogenic differentiation of PDLSCs. Irisin elevated the expression of RUNX2, ALP, and OPG while decreased the expression of RANKL in PDLSCs. Irisin ameliorated the alveolar bone loss, suppressed cytokine levels, and increased OPG/RANKL expression ratio in rat with periodontitis and orthodontic tooth movement. Irisin prevented alveolar bone destruction during OTM in rats with periodontitis.

UAV multispectral multi-domain feature optimization for the air-to-ground recognition of outdoor injured human targets under cross-scene environment.

Objective: UAV-based multispectral detection and identification technology for ground injured human targets, is a novel and promising unmanned technology for public health and safety IoT applications, such as outdoor lost injured searching and battlefield casualty searching, and our previous research has demonstrated its feasibility. However, in practical applications, the searched human target always exhibits low target-background contrast relative to the vast and diverse surrounding environment, and the ground environment also shifts randomly during the UAV cruise process. These two key factors make it difficult to achieve highly robust, stable, and accurate recognition performance under the cross-scene situation. Methods: This paper proposes a cross-scene multi-domain feature joint optimization (CMFJO) for cross-scene outdoor static human target recognition. Results: In the experiments, we first investigated the impact severity of the cross-scene problem and the necessity to solve it by designing 3 typical single-scene experiments. Experimental results show that although a single-scene model holds good recognition capability for its scenes (96.35% in desert scenes, 99.81% in woodland scenes, and 97.39% in urban scenes), its recognition performance for other scenes deteriorates sharply (below 75% overall) after scene changes. On the other hand, the proposed CMFJO method was also validated using the same cross-scene feature dataset. The recognition results for both individual scene and composite scene show that this method could achieve an average classification accuracy of 92.55% under cross-scene situation. Discussion: This study first tried to construct an excellent cross-scene recognition model for the human target recognition, named CMFJO method, which is based on multispectral multi-domain feature vectors with scenario-independent, stable and efficient target recognition capability. It will significantly improve the accuracy and usability of UAV-based multispectral technology method for outdoor injured human target search in practical applications and provide a powerful supporting technology for public safety and health.

Survival benefits of para-aortic lymphadenectomy in colorectal cancer with clinically suspected para-aortic lymph node metastasis: a meta-analysis and systematic review.

BACKGROUND AND OBJECTIVES: In patients with colorectal cancer and clinically suspected para-aortic lymph node metastasis, the survival benefit of para-aortic lymphadenectomy is unknown. We conducted a meta-analysis and systematic review to investigate it. METHODS: PubMed, Web of Science, and EMBASE were searched until January 2000 to April 2022 to identify studies reporting overall survivals, complication rates, and hazard ratios of prognostic factors in patients with colorectal cancer undergoing para-aortic lymphadenectomy, and those data were pooled. RESULTS: Twenty retrospective studies (1021 patients undergoing para-aortic lymphadenectomy) met the inclusion criteria. Meta-analysis indicates that participants undergoing para-aortic lymphadenectomy were associated with 5-year survival benefit, compared to those not receiving para-aortic lymphadenectomy (odds ratio = 3.73, 95% confidence interval: 2.05-6.78), but there was no significant difference in complication rate (odds ratio = 0.97, 95% confidence interval: 0.46-2.08). Further analysis of para-aortic lymphadenectomy group showed that 5-year survival of the positive group with pathologically para-aortic lymph node metastasis was lower than that of the negative group (odds ratio = 0.19, 95% confidence interval: 0.11-0.31). Moreover, complete resection (odds ratio = 5.26, 95% confidence interval: 2.02-13.69), para-aortic lymph node metastasis (≤4) (hazard ratio = 1.88, 95% confidence interval: 0.97-3.62), and medium-high differentiation (hazard ratio = 2.98, 95% confidence interval: 1.48-5.99) were protective factors for survival. Preoperative extra-retroperitoneal metastasis was associated with poorer relapse-free survival (hazard ratio = 1.85, 95% confidence interval: 1.10-3.10). CONCLUSION: Para-aortic lymphadenectomy had promising clinical efficacy in prolonging survival rather than complication rate in patients with colorectal cancer and clinically diagnostic para-aortic lymph node metastasis. Further prospective studies should be performed. TRIAL REGISTRATION: PROSPERO: CRD42022379276.

Application of immune checkpoint inhibitors in immunotherapy for gastric cancer.

Gastric cancer is the fifth most common cancer worldwide. With the development of immunotherapy, especially the application of immune checkpoint inhibitors (ICIs), the prognosis of advanced gastric cancer has improved. At present, ICIs combined with other therapies or dual ICI strategies in the treatment of advanced gastric cancer have shown clinical effectiveness and controllable safety. In addition, predictive biomarkers facilitate the precise selection of patients. Therefore, it is crucial to explore rational combinations and reliable predictive biomarkers for ICI therapy. This article reviews the recent advances in ICIs and relevant predictive biomarkers in the treatment of gastric cancer.

In recent years, with the application of immunotherapy, clinical efficacy in gastric cancer has been effectively improved. At present, it is encouraging that immunotherapy combined with chemotherapy has become the first choice for the treatment of patients with advanced gastric cancer. However, researchers remain committed to exploring the efficacy of immunotherapy in combination with various therapies. Equally important, the identification of biomarkers can facilitate the selection of patients suitable for immunotherapy. This article summarizes important immunotherapy clinical trials and discusses therapeutic combinations and biomarkers being explored.

Artificial intelligence can use physiological parameters to optimize treatment strategies and predict clinical deterioration of sepsis in ICU.

Objective.Sepsis seriously threatens human life. Early identification of a patient's risk status and appropriate treatment can reduce septic shock risk and mortality. Our purpose is to design and validate an adjunctive therapy system based on deep reinforcement learning (DRL), which can provide treatment recommendations with providence and assess the patient's risk status and treatment options in the early stages.Approach.Data is from the Beth Israel Deaconess Medical Center. The raw data included 53 423 patients from MIMIC-III. Of these, 19 620 eligible samples were screened to form the final cohort. First, the patient's physiological parameters were fed into the DRL therapy strategy recommendation module (TSRM), which provides a forward-looking recommendation for treatment strategy. The recommended strategies were then fed into the reinforcement learning risk assessment module (RAM), which predicts the patient's risk status and treatment strategy from a long-term perspective. The DRL model designed in this paper assists in formulating treatment plans and evaluating treatment risks and patient status through continuous interaction with patient trajectory; this model therefore has the foresight that a supervising deep learning model does not.Main results.The experiment shows that, in the test set for the TSRM, mortality is the lowest when the treatment strategy that is actually implemented is the same as the AI-recommended strategy. Regarding the RAM, it can accurately grasp a patient's deterioration trend, and can reasonably assess a patient's risk status and treatment plans at an early stage. The assessment results of the model were matched with the actual clinical records.Significance.A DRL-based sepsis adjunctive therapy model is proposed. It can prospectively assist physicians in proposing treatment strategies, assess the patient's risk status and treatment methods early on, and detect deterioration trends in advance.

HDAC5-Mediated Acetylation of p100 Suppresses Its Processing.

INTRODUCTION: Periodontitis is a condition involving chronic inflammation in the gums, periodontal ligaments, cementum, and alveolar bone. Nuclear factor-κB (NF-κB) activation is the prominent mediator of inflammation and osteoclast differentiation. The role of histone deacetylase 5 (HDAC5) in periodontitis development and NF-κB regulation is not fully understood. METHODS: We used primary mouse bone marrow-derived osteoclast cultures in vitro and a mouse model of chronic periodontists (CPD) treated with the HDAC4/5 inhibitor LMK-235. Real-time polymerase chain reaction, micro computed tomography, flow cytometry, western blot, and immunoprecipitation were used to study proinflammatory cytokines, NF-κB activation, HDAC5 activity, and the interaction of HDAC5 with NF-κB p100. RESULTS: LMK-235, a selective inhibitor of HDAC4 and HDAC5, reduced osteoclast marker gene expression (Cstk, Acp5, and Calcr) and tartrate-resistant acid phosphatase activity in primary osteoclast cultures. LMK-235 reduced the increase in cementoenamel junction-alveolar bone crest distance, inflammatory cell infiltration of gingival tissues, and expression levels of interleukin (IL)-1ß, tumor necrosis factor alpha, IL-6, and IL-23a, indicating an ameliorative effect on CPD. Immunoprecipitation experiments have further confirmed p100-HDAC5 interaction, acetylation levels of p100, and NF-κB activation. CONCLUSIONS: These results indicate that HDAC5 binds and deacetylates p100, leading to its activation, increased proinflammatory cytokine production, gingival infiltration, and osteoclast differentiation, thus promoting alveolar bone resorption. HDAC5 inhibition is therefore a potentially promising therapeutic strategy for the treatment of periodontitis.

Contactless multiscale measurement of cardiac motion using biomedical radar sensor.

Introduction: A contactless multiscale cardiac motion measurement method is proposed using impulse radio ultra-wideband (IR-UWB) radar at a center frequency of 7.29 GHz. Motivation: Electrocardiograph (ECG), heart sound, and ultrasound are traditional state-of-the-art heartbeat signal measurement methods. These methods suffer from defects in contact and the existence of a blind information segment during the cardiogram measurement. Methods: Experiments and analyses were conducted using coarse-to-fine scale. Anteroposterior and along-the-arc measurements were taken from five healthy male subjects (aged 25-43) when lying down or prone. In every measurement, 10 seconds of breath-holding data were recorded with a radar 55 cm away from the body surface, while the ECG was monitored simultaneously as a reference. Results: Cardiac motion detection from the front was superior to that from the back in amplitude. In terms of radar detection angles, the best cardiac motion information was observed at a detection angle of 120°. Finally, in terms of cardiac motion cycles, all the ECG information, as well as short segments of cardiac motion details named blind ECGs segments, were detected. Significance: A contactless and multiscale cardiac motion detection method is proposed with no blind detection of segments during the entire cardiac cycle. This paves the way for a potentially significant method of fast and accurate cardiac disease assessment and diagnosis that exhibits promising application prospects in contactless online cardiac monitoring and in-home healthcare.

Correlation Analysis of miR-1246 Expression in Saliva of Patients with Chronic Periodontitis and Periodontal Indexes, Inflammatory Cytokines, and Protease Molecules.

Objective: The study aimed to investigate the correlation of miR-1246 in saliva with periodontal indicators, inflammatory cytokines, and protease molecules in patients with chronic periodontitis. Methods: Thirty-five patients with chronic periodontitis were included as the chronic periodontitis group, and 35 healthy individuals were selected as the healthy control group during the same period. The miR-1246 levels, inflammatory cytokine interleukin (IL)-1ß, IL-6, IL-17, tumor necrosis factor-α (TNF-α), matrix metalloproteinase (MMP-1), MMP-8, and MMP tissue inhibitor (TIMP-1) in saliva were determined, and periodontal indexes, including the plaque index (PLI), bleeding index (BI), periodontal probing depth (PD), and attachment loss (AL) were examined. Results: The salivary levels of miR-1246, IL-1ß, IL-6, IL-17, TNF-α, MMP-1, MMP-8, and TIMP-1 and the periodontal indexes PLI, GI, PD, and AL in the chronic periodontitis group were significantly higher than those in the healthy control (P < 0.05). Salivary levels of miR-1246 in patients with chronic periodontitis were positively correlated with the levels of IL-1ß, IL-6, IL-17, TNF-α, MMP-1, MMP-8, TIMP-1, PLI, GI, PD, and AL (P < 0.05). Conclusion: Abnormally elevated levels of miR-1246 in saliva of patients with chronic periodontitis correlate with levels of periodontal indices, inflammatory cytokines, and protease molecules.

Evaluation of potentially inappropriate medications in older patients admitted to the cardiac intensive care unit according to the 2019 Beers criteria, STOPP criteria version 2 and Chinese criteria.

WHAT IS KNOWN AND OBJECTIVES: Potential inappropriate medications (PIMs) can increase the risk of medication-induced harm. However, there are no studies regarding PIMs in older and critically ill patients with cardiovascular diseases in China. Therefore, studies evaluating PIMs in these patients can help in the implementation of more effective interventions to reduce the risk of drug use. Our objective was to analyse the prevalence of PIMs in elderly patients admitted to the cardiac intensive care unit (CICU) comparing the 2019 Beers criteria (Beers criteria), Screening Tool of Older People's Potentially Inappropriate Prescriptions (STOPP) criteria version 2 (STOPP criteria) and criteria of potentially inappropriate medications for older adults in China (Chinese criteria); and analyse the factors influencing the PIMs. METHODS: This cross-sectional and retrospective study was performed with elderly patients (≥65 years) admitted to the CICU of the Beijing Tongren Hospital in China from January 2019 to June 2020. The PIMs were identified based on the Chinese, STOPP and Beers criteria at admission and discharge. The three criteria were compared using the Kappa statistic. Multiple regression analysis was used to investigate the influencing factors associated with PIMs. RESULTS AND DISCUSSION: A total of 369 patients who met the inclusion/exclusion criteria were included in this study. According to the three criteria used to evaluate the PIMs, the prevalence was 78.3% and 72.6% at admission and discharge, respectively. The prevalence rate of PIMs determined by the Chinese criteria was 62.1% at admission versus 56.6% at discharge (p = 0.134); the Beers criteria was 53.9% at admission versus 46.9% at discharge (p = 0.056); by the STOPP criteria was 20.6% at admission versus 13.8% at discharge (p = 0.015). Moreover, 28.9% (STOPP criteria), 56.8% (Beers criteria) and 73.4% (Chinese criteria) of patients taking PIMs on admission still had the same problem at discharge. The most common PIMs screened by the Beers, STOPP and Chinese criteria were diuretics, benzodiazepines and clopidogrel, respectively. Besides, the three criteria showed poor agreement. Finally, the stronger predictor of PIMs was the increased number of medications (p < 0.05). WHAT IS NEW AND CONCLUSION: The prevalence of PIMs in elderly patients admitted to the CICU was high. The Chinese, STOPP and Beers criteria are effective screening tools to detect PIMs, but the consistency between them was poor. The increased number of medications was a significant predictor of PIMs.

The Expression of PPAR Pathway-Related Genes Can Better Predict the Prognosis of Patients with Colon Adenocarcinoma.

The postoperative survival time and quality of life of patients with colon adenocarcinoma (COAD) varies widely. In order to make accurate decisions after surgery, clinicians need to distinguish patients with different prognostic trends. However, we still lack effective methods to predict the prognosis of COAD patients. Accumulated evidences indicated that the inhibition of peroxisome proliferator-activated receptors (PPARs) and a portion of their target genes were associated with the development of COAD. Our study found that the expression of several PPAR pathway-related genes were linked to the prognosis of COAD patients. Therefore, we developed a scoring system (named PPAR-Riskscore) that can predict patients' outcomes. PPAR-Riskscore was constructed by univariate Cox regression based on the expression of 4 genes (NR1D1, ILK, TNFRSF1A, and REN) in tumor tissues. Compared to typical TNM grading systems, PPAR-Riskscore has better predictive accuracy and sensitivity. The reliability of the system was tested on six external validation datasets. Furthermore, PPAR-Riskscore was able to evaluate the immune cell infiltration and chemotherapy sensitivity of each tumor sample. We also combined PPAR-Riskscore and clinical features to create a nomogram with greater clinical utility. The nomogram can help clinicians make precise treatment decisions regarding the possible long-term survival of patients after surgery.

Inhibition of nuclear factor kappa B inducing kinase suppresses inflammatory responses and the symptoms of chronic periodontitis in a mouse model.

Chronic periodontitis is an inflammatory disease that represents a major public health issue nowadays. Here, we investigated the protective role of nuclear factor kappa B (NF-κB) inducing kinase (NIK)-inhibitor on chronic periodontitis and revealed the underlying molecular mechanism. NIK-inhibitor was synthesized, and its functions were examined in primary osteoclasts and wild-type (WT) and NIK-/- chronic periodontitis mouse model. Lipopolysaccharides (LPS) or activator of NF-κB was applied to stimulate inflammatory response of osteoclasts. The qRT-PCR, ELISA and Western blot were used to measure the expression of pro-inflammatory and osteoclast-related genes, and the activation of NF-κB signaling. Osteoclastogenesis and bone damage were detected by TRAP staining and micro-CT. NIK knockdown mice had lower expression of osteoclast-related genes and improved CEJ-ABC damage. Similarly, NIK-inhibitor administration inhibited inflammatory responses and CEJ-ABC damage in chronic periodontitis models. NIK-inhibitor suppressed osteoclastogenesis and osteoclast-related genes expression through inhibiting the non-canonical NF-κB signaling. NIK plays important role in bone destruction of chronic periodontitis and NIK-inhibitor represents a promising therapeutic strategy for this disease.

Agricultural impacts drive longitudinal variations of riverine water quality of the Aral Sea basin (Amu Darya and Syr Darya Rivers), Central Asia.

River ecosystems are under increasing stress in the background of global change and ever-growing anthropogenic impacts in Central Asia. However, available water quality data in this region are insufficient for a reliable assessment of the current status, which come as no surprise that the limited knowledge of regulating processes for further prediction of solute variations hinders the development of sustainable management strategies. Here, we analyzed a dataset of various water quality variables from two sampling campaigns in 2019 in the catchments of two major rivers in Central Asia-the Amu Darya and Syr Darya Rivers. Our results suggested high spatial heterogeneity of salinity and major ion components along the longitudinal directions in both river catchments, pointing to an increasing influence of human activities toward downstream areas. We linked the modeling outputs from the global nutrient model (IMAGE-GNM) to riverine nutrients to elucidate the effect of different natural and anthropogenic sources in dictating the longitudinal variations of the riverine nutrient concentrations (N and P). Diffuse nutrient loadings dominated the export flux into the rivers, whereas leaching and surface runoff constituted the major fractions for N and P, respectively. Discharge of agricultural irrigation water into the rivers was the major cause of the increases in nutrients and salinity. Given that the conditions in Central Asia are highly susceptible to climate change, our findings call for more efforts to establish holistic management of water quality.

Influence of land use and change in the proportion of electron donors required for denitrification on N2O in groundwater.

Nitrate (NO3-) and nitrous oxide (N2O) accumulate in groundwater in relation to human activities and pose multiple threats to the global environment (harming human health and atmospheric damage). This study focused on the evaluation of groundwater NO3-, N2O, and its indirect emission factor under different land use types (agricultural land, urban land, and forest) and response mechanism of major anions to dissolved N2O within groundwater in Dexing which has the largest copper mine in Asia. Specifically, this work used self-organizing maps (SOMs) to identify which anion conditions (NO3-, SO42-, F-, Cl-) and water quality parameters were suitable for the accumulation of groundwater N2O. Finally, we found that the shallow groundwater of agricultural land has a high concentration of NO3- and N2O and the agricultural activity has a significant effect on the temporal and spatial variation of N2O in groundwater. The result of SOMs combined with the positive correlation between N2O and NO3-/SO42- suggested that the electron donor required for denitrification has a significant effect on N2O accumulation. In this respect, when an increased proportion of reduced sulfur is available as an electron donor for autotrophic denitrification, this results in lower concentrations of N2O in groundwater. Through the comprehensive evaluation of the anion conditions and N2O in groundwater under different land use types, this study case can help to estimate the N2O indirect emission from groundwater, so as to constrain the global nitrogen budget.