Aberrant dynamic functional network connectivity in progressive supranuclear palsy.

BACKGROUND: The clinical symptoms of progressive supranuclear palsy (PSP) may be mediated by aberrant dynamic functional network connectivity (dFNC). While earlier research has found altered functional network connections in PSP patients, the majority of those studies have concentrated on static functional connectivity. Nevertheless, in this study, we sought to evaluate the modifications in dynamic characteristics and establish the correlation between these disease-related changes and clinical variables. METHODS: In our study, we conducted a study on 53 PSP patients and 65 normal controls. Initially, we employed a group independent component analysis (ICA) to derive resting-state networks (RSNs), while employing a sliding window correlation approach to produce dFNC matrices. The K-means algorithm was used to cluster these matrices into distinct dynamic states, and then state analysis was subsequently employed to analyze the dFNC and temporal metrics between the two groups. Finally, we made a correlation analysis. RESULTS: PSP patients showed increased connectivity strength between medulla oblongata (MO) and visual network (VN) /cerebellum network (CBN) and decreased connections were found between default mode network (DMN) and VN/CBN, subcortical cortex network (SCN) and CBN. In addition, PSP patients spend less fraction time and shorter dwell time in a diffused state, especially the MO and SCN. Finally, the fraction time and mean dwell time in the distributed connectivity state (state 2) is negatively correlated with duration, bulbar and oculomotor symptoms. DISCUSSION: Our findings were that the altered connectivity was mostly concentrated in the CBN and MO. In addition, PSP patients had different temporal dynamics, which were associated with bulbar and oculomotor symptoms in PSPRS. It suggest that variations in dynamic functional network connectivity properties may represent an essential neurological mechanism in PSP.

Clinical and multimodal imaging features of adult-onset neuronal intranuclear inclusion disease.

OBJECTIVES: This study aimed to analyze the clinical and multimodal imaging manifestations of adult-onset neuronal intranuclear inclusion disease (NIID) patients and to investigate NIID-specific neuroimaging biomarkers. METHODS: Forty patients were retrospectively enrolled from the Qilu Hospital of Shandong University. We analyzed the clinical and imaging characteristics of 40 adult-onset NIID patients and investigated the correlation between these characteristics and genetic markers and neuropsychological scores. We further explored NIID-specific alterations using multimodal imaging indices, including diffusion tensor imaging (DTI), magnetic resonance spectroscopy (MRS), and brain age estimation. In addition, we summarized the dynamic evolution pattern of NIID by examining the changes in diffusion weighted imaging (DWI) signals over time. RESULTS: The NIID patients' ages ranged from 31 to 77 years. Cognitive impairment was the most common symptom (30/40, 75.0%), while some patients (18/40, 45.0%) initially presented with episodic symptoms such as headache (10/40, 25.0%). Patients with cognitive impairment symptoms had more cerebral white matter damage (χ2 = 11.475, P = 0.009). The most prevalent imaging manifestation was a high signal on DWI in the corticomedullary junction area, which was observed in 80.0% (32/40) of patients. In addition, the DWI dynamic evolution patterns could be classified into four main patterns. Diffusion tensor imaging (DTI) revealed extensive thinning of cerebral white matter fibers. The estimated brain age surpassed the patient's chronological age, signifying advanced brain aging in NIID patients. CONCLUSIONS: The clinical manifestations of NIID exhibit significant variability, usually leading to misdiagnosis. Our results provided new imaging perspectives for accurately diagnosing and exploring this disease's neuropathological mechanisms.

AI-Driven Diagnostic Assistance in Medical Inquiry: Reinforcement Learning Algorithm Development and Validation.

BACKGROUND: For medical diagnosis, clinicians typically begin with a patient's chief concerns, followed by questions about symptoms and medical history, physical examinations, and requests for necessary auxiliary examinations to gather comprehensive medical information. This complex medical investigation process has yet to be modeled by existing artificial intelligence (AI) methodologies. OBJECTIVE: The aim of this study was to develop an AI-driven medical inquiry assistant for clinical diagnosis that provides inquiry recommendations by simulating clinicians' medical investigating logic via reinforcement learning. METHODS: We compiled multicenter, deidentified outpatient electronic health records from 76 hospitals in Shenzhen, China, spanning the period from July to November 2021. These records consisted of both unstructured textual information and structured laboratory test results. We first performed feature extraction and standardization using natural language processing techniques and then used a reinforcement learning actor-critic framework to explore the rational and effective inquiry logic. To align the inquiry process with actual clinical practice, we segmented the inquiry into 4 stages: inquiring about symptoms and medical history, conducting physical examinations, requesting auxiliary examinations, and terminating the inquiry with a diagnosis. External validation was conducted to validate the inquiry logic of the AI model. RESULTS: This study focused on 2 retrospective inquiry-and-diagnosis tasks in the emergency and pediatrics departments. The emergency departments provided records of 339,020 consultations including mainly children (median age 5.2, IQR 2.6-26.1 years) with various types of upper respiratory tract infections (250,638/339,020, 73.93%). The pediatrics department provided records of 561,659 consultations, mainly of children (median age 3.8, IQR 2.0-5.7 years) with various types of upper respiratory tract infections (498,408/561,659, 88.73%). When conducting its own inquiries in both scenarios, the AI model demonstrated high diagnostic performance, with areas under the receiver operating characteristic curve of 0.955 (95% CI 0.953-0.956) and 0.943 (95% CI 0.941-0.944), respectively. When the AI model was used in a simulated collaboration with physicians, it notably reduced the average number of physicians' inquiries to 46% (6.037/13.26; 95% CI 6.009-6.064) and 43% (6.245/14.364; 95% CI 6.225-6.269) while achieving areas under the receiver operating characteristic curve of 0.972 (95% CI 0.970-0.973) and 0.968 (95% CI 0.967-0.969) in the scenarios. External validation revealed a normalized Kendall τ distance of 0.323 (95% CI 0.301-0.346), indicating the inquiry consistency of the AI model with physicians. CONCLUSIONS: This retrospective analysis of predominantly respiratory pediatric presentations in emergency and pediatrics departments demonstrated that an AI-driven diagnostic assistant had high diagnostic performance both in stand-alone use and in simulated collaboration with clinicians. Its investigation process was found to be consistent with the clinicians' medical investigation logic. These findings highlight the diagnostic assistant's promise in assisting the decision-making processes of health care professionals.

Effects of Bacterial Biofilm on Regulation of Neurovascular Unit Functions and Neuroinflammation of Patients with Ischemic Cerebral Stroke by Immunocyte.

In this experiment, the effects of biofilm on neurovascular unit functions and neuroinflammation of patients with ischemic cerebral stroke were investigated. For this purpose, 20 adult male rats were purchased from Taconic (8 to 10 weeks old, weighing between 20 and 24g) and selected as the research objects. Then, they were randomly divided into an experimental group (10 rats) and a control group (10 rats). Ischemic cerebral stroke rat models were established. Besides, pseudomonas aeruginosa (PAO1) was prepared manually and implanted into the bodies of rats in the experimental group. mNSS scores, cerebral infarction area, and the release of inflammatory cytokines of rats in the two groups were compared. Results showed that mNSS scores for rats in the experimental group at all periods were remarkably higher than those for rats in the control group (P<0.05), which demonstrated that the rats in the experimental group suffered much severer neurological impairment than those in the control group. In addition, the release of tumor necrosis factor (TNF)-α, interleukin (IL)-6, IL-1ß, inducible nitric oxide synthase (iNOS), and IL-10 were all higher than those of the control group (P<0.05). The cerebral infarction area of the experimental group at all periods was remarkably larger than that of the control group (P<0.05). In conclusion, the formation of biofilm led to the aggravation of neurological impairment and inflammatory reactions among patients with ischemic cerebral stroke.

Detailed Structural Analysis of the Immunoregulatory Polysaccharides from the Mycobacterium Bovis BCG.

Bacillus Calmette-Guérin polysaccharide and nucleic acid (BCG-PSN), extracted from Mycobacterium bovis, is an immunoregulatory medicine commonly used in clinic. However, the structural characteristics and potential pharmacological efficacy of the polysaccharides from BCG-PSN remain unclear. Herein, two polysaccharides (BCG-1 and BCG-2) were purified and their structures were characterized. Monosaccharide composition analysis combined with methylation analysis and NMR data indicated that BCG-1 and BCG-2 were an α-D-(1→4)-mannan with (1→2)-linked branches, and an α-D-(1→4)-glucan with (1→6)-linked branches, respectively. Herein, the mannan from BCG-PSN was first reported. Bioactivity assays showed that BCG-1 and BCG-2 dose-dependently and potently increased the production of inflammatory mediators (NO, TNF-α, IL-6, IL-1ß, and IL-10), as well as their mRNA expressions in RAW264.7 cells; both have similar or stronger effects compared with BCG-PSN injection. These data suggest that BCG-1 and BCG-2 are very likely the active ingredients of BCG-PSN.

Predicting temporal propagation of seasonal influenza using improved gaussian process model.

Influenza rapidly spreads in seasonal epidemics and imposes a considerable economic burden on hospitals and other healthcare costs. Thus, predicting the propagation of influenza accurately is crucial in preventing influenza outbreaks and protecting public health. Most current studies focus on the spread simulation of influenza. However, few studies have investigated the dependencies between meteorological variables and influenza activity. This study develops a non-parametric model based on Gaussian process regression for influenza prediction considering meteorological effect to capture temporal dependencies hidden in influenza time series. To identify the most explanatory external variables, L1-regularization is applied to identify meteorology factor subsets, and three types of covariance functions are designed to characterize non-stationary and periodic behavior in influenza activity. The dependencies of diseases and meteorology are modeled through the designed cross-covariance function. A real case in Shenzhen, China was studied to validate our proposed model along with comparisons to recently developed multivariate statistical models for influenza prediction. Results show that our proposed influenza prediction approach achieves superior performance in terms of one-week-ahead prediction of influenza-like illness.

Molecular characterization of CIMMYT maize inbred lines with genotyping-by-sequencing SNPs.

KEY MESSAGE: Molecular characterization information on genetic diversity, population structure and genetic relationships provided by this research will help maize breeders to better understand how to utilize the current CML collection. CIMMYT maize inbred lines (CMLs) have been widely used all over the world and have contributed greatly to both tropical and temperate maize improvement. Genetic diversity and population structure of the current CML collection and of six temperate inbred lines were assessed and relationships among all lines were determined with genotyping-by-sequencing SNPs. Results indicated that: (1) wider genetic distance and low kinship coefficients among most pairs of lines reflected the uniqueness of most lines in the current CML collection; (2) the population structure and genetic divergence between the Temperate subgroup and Tropical subgroups were clear; three major environmental adaptation groups (Lowland Tropical, Subtropical/Mid-altitude and Highland Tropical subgroups) were clearly present in the current CML collection; (3) the genetic diversity of the three Tropical subgroups was similar and greater than that of the Temperate subgroup; the average genetic distance between the Temperate and Tropical subgroups was greater than among Tropical subgroups; and (4) heterotic patterns in each environmental adaptation group estimated using GBS SNPs were only partially consistent with patterns estimated based on combining ability tests and pedigree information. Combining current heterotic information based on combining ability tests and the genetic relationships inferred from molecular marker analyses may be the best strategy to define heterotic groups for future tropical maize improvement. Information resulting from this research will help breeders to better understand how to utilize all the CMLs to select parental lines, replace testers, assign heterotic groups and create a core set of breeding germplasm.

Trajectory Correction and Locomotion Analysis of a Hexapod Walking Robot with Semi-Round Rigid Feet.

Aimed at solving the misplaced body trajectory problem caused by the rolling of semi-round rigid feet when a robot is walking, a legged kinematic trajectory correction methodology based on the Least Squares Support Vector Machine (LS-SVM) is proposed. The concept of ideal foothold is put forward for the three-dimensional kinematic model modification of a robot leg, and the deviation value between the ideal foothold and real foothold is analyzed. The forward/inverse kinematic solutions between the ideal foothold and joint angular vectors are formulated and the problem of direct/inverse kinematic nonlinear mapping is solved by using the LS-SVM. Compared with the previous approximation method, this correction methodology has better accuracy and faster calculation speed with regards to inverse kinematics solutions. Experiments on a leg platform and a hexapod walking robot are conducted with multi-sensors for the analysis of foot tip trajectory, base joint vibration, contact force impact, direction deviation, and power consumption, respectively. The comparative analysis shows that the trajectory correction methodology can effectively correct the joint trajectory, thus eliminating the contact force influence of semi-round rigid feet, significantly improving the locomotion of the walking robot and reducing the total power consumption of the system.

Genome-wide loss of 5-hmC is a novel epigenetic feature of Huntington's disease.

5-Hydroxymethylcytosine (5-hmC) may represent a new epigenetic modification of cytosine. While the dynamics of 5-hmC during neurodevelopment have recently been reported, little is known about its genomic distribution and function(s) in neurodegenerative diseases such as Huntington's disease (HD). We here observed a marked reduction of the 5-hmC signal in YAC128 (yeast artificial chromosome transgene with 128 CAG repeats) HD mouse brain tissues when compared with age-matched wild-type (WT) mice, suggesting a deficiency of 5-hmC reconstruction in HD brains during postnatal development. Genome-wide distribution analysis of 5-hmC further confirmed the diminishment of the 5-hmC signal in striatum and cortex in YAC128 HD mice. General genomic features of 5-hmC are highly conserved, not being affected by either disease or brain regions. Intriguingly, we have identified disease-specific (YAC128 versus WT) differentially hydroxymethylated regions (DhMRs), and found that acquisition of DhmRs in gene body is a positive epigenetic regulator for gene expression. Ingenuity pathway analysis (IPA) of genotype-specific DhMR-annotated genes revealed that alternation of a number of canonical pathways involving neuronal development/differentiation (Wnt/ß-catenin/Sox pathway, axonal guidance signaling pathway) and neuronal function/survival (glutamate receptor/calcium/CREB, GABA receptor signaling, dopamine-DARPP32 feedback pathway, etc.) could be important for the onset of HD. Our results indicate that loss of the 5-hmC marker is a novel epigenetic feature in HD, and that this aberrant epigenetic regulation may impair the neurogenesis, neuronal function and survival in HD brain. Our study also opens a new avenue for HD treatment; re-establishing the native 5-hmC landscape may have the potential to slow/halt the progression of HD.

Genome-wide mapping of 5-hydroxymethylcytosine in three rice cultivars reveals its preferential localization in transcriptionally silent transposable element genes.

5-Hydroxymethylcytosine (5hmC), a modified form of cytosine that is considered the sixth nucleobase in DNA, has been detected in mammals and is believed to play an important role in gene regulation. In this study, 5hmC modification was detected in rice by employing a dot-blot assay, and its levels was further quantified in DNA from different rice tissues using liquid chromatography-multistage mass spectrometry (LC-MS/MS/MS). The results showed large intertissue variation in 5hmC levels. The genome-wide profiles of 5hmC modification in three different rice cultivars were also obtained using a sensitive chemical labelling followed by a next-generation sequencing method. Thousands of 5hmC peaks were identified, and a comparison of the distributions of 5hmC among different rice cultivars revealed the specificity and conservation of 5hmC modification. The identified 5hmC peaks were significantly enriched in heterochromatin regions, and mainly located in transposable elements (TEs), especially around retrotransposons. The correlation analysis of 5hmC and gene expression data revealed a close association between 5hmC and silent TEs. These findings provide a resource for plant DNA 5hmC epigenetic studies and expand our knowledge of 5hmC modification.

Person re-identification based on multi-branch visual transformer and self-distillation.

Person re-identification technology has made significant progress in recent years with the development of deep learning. However, the recognition rate of models in this field is still lower than that of face recognition, which is challenging to implement in practical application scenarios. Therefore, improving the recognition rate of the pedestrian re-identification model is still a critical task. This paper mainly focuses on three aspects of this problem. The first is to use the characteristics of the multi-branch network structure of person re-identification to dig out the most effective online self-distillation scheme between branches without increasing additional resource requirements, making full use of the information contained in each branch. Secondly, this paper analyzes and verifies the pros and cons of knowledge distillation based on mean squared error (MSE) loss function and Kullback-Leibler (KL) divergence from theoretical and experimental perspectives. Finally, we verified through experiments that adding a specific value of noise perturbation to the model weights can further improve the recognition rate of the model. After several improvements in these areas, we obtained the current state-of-the-art performance on four public datasets for person re-identification.

Transcriptional expression patterns of the cortical morphometric similarity network in progressive supranuclear palsy.

BACKGROUND: It has been demonstrated that progressive supranuclear palsy (PSP) correlates with structural abnormalities in several distinct regions of the brain. However, whether there are changes in the morphological similarity network (MSN) and the relationship between changes in brain structure and gene expression remain largely unknown. METHODS: We used two independent cohorts (discovery dataset: PSP: 51, healthy controls (HC): 82; replication dataset: PSP: 53, HC: 55) for MSN analysis and comparing the longitudinal changes in the MSN of PSP. Then, we applied partial least squares regression to determine the relationships between changes in MSN and spatial transcriptional features and identified specific genes associated with MSN differences in PSP. We further investigated the biological processes enriched in PSP-associated genes and the cellular characteristics of these genes, and finally, we performed an exploratory analysis of the relationship between MSN changes and neurotransmitter receptors. RESULTS: We found that the MSN in PSP patients was mainly decreased in the frontal and temporal cortex but increased in the occipital cortical region. This difference is replicable. In longitudinal studies, MSN differences are mainly manifested in the frontal and parietal regions. Furthermore, the expression pattern associated with MSN changes in PSP involves genes implicated in astrocytes and excitatory and inhibitory neurons and is functionally enriched in neuron-specific biological processes related to synaptic signaling. Finally, we found that the changes in MSN were mainly negatively correlated with the levels of serotonin, norepinephrine, and opioid receptors. CONCLUSIONS: These results have enhanced our understanding of the microscale genetic and cellular mechanisms responsible for large-scale morphological abnormalities in PSP patients, suggesting potential targets for future therapeutic trials.

Sensitive, precise fingerprint profiling for monosaccharide analysis of Bacillus Calmette-Guérin polysaccharide and nucleic acid isolates.

A sensitive and precise HPLC-DAD method with pre-column PMP derivatization was established and validated, for analyzing the polysaccharides in Bacillus Calmette-Guérin polysaccharide and nucleic acid (BCG-PSN) isolates, after acid hydrolysis. And the HPLC fingerprint profiling was used to analyze its monosaccharide composition. The monosaccharide concentration-peak area calibration curve was of good linearity (R2 > 0.99), over the range of 0.016-0.08 mg/mL for mannose or 0.24-1.20 mg/mL for glucose, with high recovery of 93-105 % for quality control samples. The intra-day RSD values of mannose and glucose concentration were less than 2.5 % and 2.1 %, respectively, and their inter-day RSD values were less than 4.3 % and 2.2 %, respectively, and remained stable for up to 14 days. This method also remained durable against changes in chromatographic parameters, but it's susceptible to the flow rate of mobile phase. Additionally, the method was applied to analyze the content of mannose and glucose in 22 batches BCG-PSN powder and 17 batches BCG-PSN injection. The results showed that the HPLC-DAD fingerprint spectra of all the BCG-PSN powder and BCG-PSN injection samples had a high degree of similarity, with the similar indexes up to 0.999 and 0.998, respectively. The HPLC-DAD method with pre-column PMP derivatization is highly rapid, effective, visual, and accurate for determination of monosaccharide contents. The validated method was successfully applied to the analysis of polysaccharide in both BCG-PSN powder and injection.

Simulation insights into the lipase adsorption on zeolitic imidazolate framework-8.

Zeolitic imidazolate frameworks (ZIFs) have recently emerged as immobilization matrices for biomolecules, most notably enzymes. Understanding the key factors that dominate the enzyme's catalytic activity on/in ZIFs is crucial for the development of new immobilization matrices. In this work, a combination of the parallel tempering Monte Carlo simulation and all-atom molecular dynamics simulation is performed to study the orientation and conformation of the Candida rugose lipase (CRL) adsorbed on oppositely charged and neutral ZIF-8 (i.e., ZIF-8-COOH, ZIF-8-NH2, and ZIF-8-neutral) surfaces. The results show that CRL could adsorb on all ZIF-8 surfaces, with an ordered orientation obtained on charged ZIF-8 surfaces. ZIF-8-NH2 is a good candidate for CRL immobilization since it can maximize the catalytic activity of CRL. The native conformation of CRL is well preserved on all three surfaces due to the partially water-containing surface of ZIF-8. The results could provide theoretical support for the application of porous materials in enzyme immobilization.

SMAD7 gene polymorphisms and their influence on patients with colorectal cancer.

Colorectal cancer (CRC) is a prevalent malignant tumor, and its pathogenesis is still not fully understood. Studies have shown that SMAD7 gene polymorphisms can affect CRC susceptibility, but the results have been inconsistent and require additional confirmation. Our study aimed to evaluate the effect of SMAD7 variants on the risk of CRC in the Chinese Han population. A total of five single nucleotide polymorphisms (SNPs) in SMAD7 were genotyped among 696 CRC patients and 696 healthy participants using the MassARRAY iPLEX platform. SNPs were evaluated for their associations with CRC using logistic regression analysis under multiple genetic models. The false-positive report probability (FPRP) analysis was used to validate the positive findings. Our study indicated that rs11874392 showed an increased association with CRC risk (odds ratio, 1.31; 95% confidence interval, 1.04-1.67; p = 0.024). Stratified analysis showed that rs11874392 might increase the risk of CRC in females (OR = 1.70, p = 0.028), individuals with smoking (OR = 1.87, p = 0.026), and drinking (OR = 1.38, p = 0.027). The rs11874392 was found to be related to an elevated risk of rectal cancer (OR = 1.73, p = 0.003), but not with colon cancer. FPRP analysis demonstrated that all of these associations were statistically significant (FPRP <0.2). Additionally, rs11874392 was the strongest predictive model for CRC. This study provides evidence that the SMAD7 rs11874392 is related to an increased susceptibility to CRC.

Adverse short-term effects of ozone on cardiovascular mortalities modified by season and temperature: a time-series study.

Introduction: Ambient ozone pollution becomes critical in China. Conclusions on the short-term effects of ozone on cardiovascular mortality have been controversial and limited on cause-specific cardiovascular mortalities and their interactions with season and temperature. This research aimed to investigate the short-term effects of ozone and the modifications of season and temperature on cardiovascular mortality. Methods: Cardiovascular death records, air pollutants, and meteorological factors in Shenzhen from 2013 to 2019 were analyzed. Daily 1-h maximum of ozone and daily maximum 8-h moving average of ozone were studied. Generalized additive models (GAMs) were applied to evaluate their associations with cardiovascular mortalities in sex and age groups. Effect modifications were assessed by stratifying season and temperature. Results: Distributed lag impacts of ozone on total cardiovascular deaths and cumulative effects on mortality due to ischemic heart disease (IHD) were most significant. Population under 65 years old was most susceptible. Majority of significant effects were found in warm season, at high temperature, and at extreme heat. Ozone-associated risks in total deaths caused by hypertensive diseases reduced in warm season, while risks in IHD in males increased at high temperature. Extreme heat enhanced ozone effects on deaths caused by CVDs and IHD in the population under 65 years old. Discussion: The revealed cardiovascular impacts of ozone below current national standard of air quality suggested improved standards and interventions in China. Higher temperature, particularly extreme heat, rather than warm season, could significantly enhance the adverse effects of ozone on cardiovascular mortality in population under 65 years old.

Dynamic cytokines signature predicts survival outcome from severe Immune-related hepatitis with PD-1/PD-L1 blockade in lung cancer.

BACKGROUND: Immune-related adverse events (irAEs), particularly immune-related hepatitis (IRH) is a potentially serious complication of immune checkpoint inhibitor (ICI) therapy. This retrospective cohort study investigated potential prognostic and predictive biomarkers for IRH. METHOD: This study included 37 patients with advanced lung cancer who received ICIs and were divided into two groups: ≥Grade 3 (G3)-IRH group (n = 17) and without irAE (no-irAE) group (n = 20). Blood samples collected at three different time points and pre-treatment tumor biopsy samples were analyzed using multi-omics assays. RESULTS: The IL-1B RNA expression was significantly increased (limma, fold = 1.94) in the ≥ G3-IRH group than the no-irAE group. Compared with no-irAE group, ≥G3-IRH group had higher monocyte and eosinophil infiltration and lower macrophage infiltration, particularly macrophage M2. Transcriptomics analyses of pre-treatment tumor samples revealed significant upregulation of various inflammation-related genes in the ≥ G3-IRH group (False discovery rate < 0.05). Moreover, various proinflammatory cytokines and chemokines were significantly lower in the plasma of the ≥ G3-IRH group than in the no-irAE group. Subgroup analyses of the ≥ G3-IRH group revealed that plasma IL-1A was significantly higher among those whose IRH resolved than those who had IRH-related death. Patients who died had a greater increase in immune score and Euclidean distance from the baseline to the seventh day of IRH onset, with a dramatic increase in Euclidean distance after immunosuppression, suggesting overstimulated immune status. CONCLUSION: Our study demonstrated the association between IL-1B overexpression and IRH susceptibility. Immune score and Euclidean distance of inflammatory cytokines may provide predictive value on the survival outcome from ≥ G3 IRH.

A novel biological sources consistency evaluation method reveals high level of biodiversity within wild natural medicine: A case study of Amynthas earthworms as "Guang Dilong".

For wild natural medicine, unanticipated biodiversity as species or varieties with similar morphological characteristics and sympatric distribution may co-exist in a single batch of medical materials, which affects the efficacy and safety of clinical medication. DNA barcoding as an effective species identification tool is limited by its low sample throughput nature. In this study, combining DNA mini-barcode, DNA metabarcoding and species delimitation method, a novel biological sources consistency evaluation strategy was proposed, and high level of interspecific and intraspecific variations were observed and validated among 5376 Amynthas samples from 19 sampling points regarded as "Guang Dilong" and 25 batches of proprietary Chinese medicines. Besides Amynthas aspergillum as the authentic source, 8 other Molecular Operational Taxonomic Units (MOTUs) were elucidated. Significantly, even the subgroups within A. aspergillum revealed here differ significantly on chemical compositions and biological activity. Fortunately, this biodiversity could be controlled when the collection was limited to designated areas, as proved by 2796 "decoction pieces" samples. This batch biological identification method should be introduced as a novel concept regarding natural medicine quality control, and to offer guidelines for in-situ conservation and breeding bases construction of wild natural medicine.

Modulation based cells distribution for visible light communication.

Cells distribution for visible light communication can enhance the capacity of the data transmission by the reuse of optical spectrum. In this paper, we adopt three modulation formats as OOK, PPM and PWM for neighboring cells A, B and C respectively. The prototype experiment results demonstrate the error free transmission of 1.0 Mbit/s and 6.25 Mbit/s visible light communication system with our scheme. With the available LED, we can expect that the data rate of a visible light communication system with seamless connectivity can be up to 71.4 Mbit/s.

Arctiin elevates osteogenic differentiation of MC3T3-E1 cells by modulating cyclin D1.

Osteoporosis is a systemic disorder of bone metabolism. This study aimed to investigate the impacts and possible mechanisms of Arctiin, a lignin isolated from Arctium lappa on MC3T3-E1 osteoblast differentiation. In this study, after treatment with different concentrations of Arctiin, reverse transcription-quantitative polymerase chain reaction (RT-qPCR) and western blotting were used to estimate the expression of osteogenesis markers. Then, the activity of alkaline phosphatase (ALP) was detected by an ALP assay kit and calcium nodules staining was evaluated by alizarin red staining (ARS). Additionally, the regulatory effects of Arctiin on cyclin D1 (Ccnd1) was assessed by measurement of protein expression. Subsequently, the functions of Ccnd1 silencing on the osteogenic differentiation was examined in Arctiin-treated MC3T3-E1 cells. Results indicated that Arctiin dose-dependently upregulated the expression of runt-related transcription factor 2 (RUNX2), collagen type 1 (COL1A1), osteocalcin (OCN) and osteopontin (OPN). Elevated ALP activity and calcification degree was prominently observed in the Arctiin-treated groups. Moreover, Ccnd1 expression was notably enhanced after Arctiin intervention. Importantly, Ccnd1-knockdown abrogated the impacts of Arctiin on osteogenic differentiation of MC3T3-E1. To conclude, findings in this study suggested that Arctiin could regulate MC3T3-E1 osteoblast differentiation via up-regulating Ccnd1, supporting that Arctiin might be a therapeutic target for osteoporosis.