Aerobic exercise prevents and improves cognitive dysfunction caused by morphine withdrawal via regulating endogenous opioid peptides in the brain.

BACKGROUND: Morphine withdrawal leads to serious cognitive deficits in which dynorphins are directly involved. Recently, exercise has been shown to prevent and improve cognition dysfunction in a variety of ways. Meanwhile, exercise can regulate the endogenous opioid peptides including dynorphins. However, it remains unclear whether exercise influences cognitive dysfunction caused by morphine withdrawal via dynorphins. In the current study, we investigate the physiological mechanism of exercise prevention and improvement aganist cognition dysfunction caused by morphine withdrawal. METHODS: Male, adult C57BL/6 mice were randomly divided into 5 groups : Saline control (WT), exercise (EXE), morphine withdrawl (MW), exercise + morphine withdrawl (EMW), morphine withdrawl + exercise (MWE). We established aerobic exercise prevention/improvement models, and conducted behavioral tests including Open field test (OFT), Temporal order memory test (TOM) and Y-maze. Through Western Blotting and immunofluorescence staining, we detected endogenous opioid peptides in hippocampus and mPFC. RESULTS: Compared with MW group, EMW group and MWE group showed the same performance as WT group in TOM and Y-maze, with correct object recognition and memory ability. In Western Blotting and immunofluorescence staining experiments, it indicated that EMW group reduced the expression of PDYN and its fluorescence intensity in hippocampus; MWE group reduced the expression of OPRK1 and its fluorescence intensity in mPFC. CONCLUSION: Our data suggest that aerobic exercise can both prevent and improve cognitive dysfunction caused by acute morphine withdrawal via respectively down-regulating PDYN in the hippocampus and down-regulating OPRK1 in the mPFC. They may become new targets for drugs development in the future.

Optogenetically modified human embryonic stem cell-derived otic neurons establish functional synaptic connection with cochlear nuclei.

Spiral ganglia neurons (SGNs) impairment can cause deafness. One important therapeutic approach involves utilizing stem cells to restore impaired auditory circuitry. Nevertheless, the inadequate implementation of research methodologies poses a challenge in accurately assessing the functionality of derived cells within the circuit. Here, we describe a novel method for converting human embryonic stem cells (hESCs) into otic neurons (ONs) and assess their functional connectivity using an optogenetic approach with cells or an organotypic slice of rat cochlear nucleus (CN) in coculture. Embryonic stem cell-derived otic neurons (eONs) exhibited SGN marker expression and generated functional synaptic connection when cocultured with cochlear nucleus neurons (CNNs). Synapsin 1 and VGLUT expression are found in the cochlear nucleus of brain slices, where eONs projected processes during the coculture of eONs and CN brain slices. Action potential spikes and INa+/IK+ of CNNs increased in tandem with light stimulations to eONs. These findings provide further evidence that eONs may be a candidate source to treat SGN-deafness.

WNT16 as a promising biomarker for systemic lupus erythematosus and its role in regulating cell proliferation and apoptosis.

OBJECTIVES: To investigate the expression and function of WNT16, a member of the WNT family protein, in the context of systemic lupus erythematosus (SLE). METHODS: WNT16 expression was assessed in peripheral blood mononuclear cells (PBMCs) from 35 SLE patients and 25 healthy individuals using quantitative polymerase chain reaction. Additionally, serum WNT16 protein levels were quantified via enzyme-linked immunosorbent assay in 162 SLE patients, 96 healthy controls (HC), and disease controls comprised 154 individuals with rheumatoid arthritis (RA) and Sjögren's syndrome (SS). We investigated the associations between WNT16 protein levels and clinical manifestations, laboratory indices, and disease activity in SLE patients. Receiver operating characteristic (ROC) curve analysis was employed to evaluate the diagnostic potential of serum WNT16 for SLE. Furthermore, we performed a knockdown assay on Jeko-1 cells and assessed cell proliferation and apoptosis using Cell Counting Kit-8 and flow cytometry. RESULTS: WNT16 mRNA in SLE patients' PBMCs were significantly lower than those in HC. Furthermore, serum WNT16 in SLE patients were markedly reduced compared to HC, RA, and SS cohorts. ROC curve analysis indicated that plasma WNT16 levels could serve as a potential biomarker for SLE identification (AUC=0.809, SLE vs. HC; AUC=0.760, SLE vs. RA; AUC=0.710, SLE vs. SS). Notably, a weak positive correlation was observed between WNT16 protein and both alkaline phosphatase and lymphocyte percentages. Conversely, a weak negative correlation existed between WNT16 and low-density lipoprotein, neutrophil percentage, and the incidence of pleurisy and disease activity. Additionally, our study confirmed that WNT16 knockdown impairs cell proliferation and enhances apoptosis. CONCLUSIONS: Serum WNT16 levels effectively differentiate SLE patients from healthy controls and individuals with other autoimmune disorders. WNT16 serves as a potential biomarker with high sensitivity. The diminished expression of WNT16 in SLE may have a significant role in its pathogenesis through the regulation of cell proliferation and apoptosis.

Investigation on Anti-Fuel Erosion Performance of Sasobit/SBS-Modified Asphalt and Its Mixtures.

The fuel leakage of fuel vehicles will exacerbate the occurrence of distresses on asphalt pavements, including peeling, chipping and potholes, especially under the synergistic effect of traffic load and environment. In this research, Sasobit, which is commonly used as a warm agent in asphalt, is selected as the anti-fuel erosion agent and incorporated into SBS-modified asphalt and its mixtures. Diesel and gasoline are selected as the fuel erosion media. Sasobit/SBS-modified asphalt binder and its mixtures are investigated for fuel erosion. The rheological properties of bitumen and the mechanical properties of asphalt mixtures are assessed. The experimental findings show that the dissolution velocity of SBS-modified asphalt with 3% Sasobit is 0.2%/min for diesel erosion, while it is 1.7%/min for gasoline erosion, lower than the control sample without Sasobit. Meanwhile, the rutting factor of Sasobit/SBS-modified asphalt decreases less than that of the control sample without Sasobit. Furthermore, the mass loss ratio after the Cantabro test of Sasobit/SBS-modified asphalt mixtures is 1.2% for diesel erosion, while it is 6.8% for gasoline erosion, lower than that of the control sample without Sasobit. The results of the mechanical properties for asphalt mixtures demonstrate that Sasobit can enhance the anti-fuel erosion performance. Moreover, the research results of the Sasobit modification mechanism show that Sasobit can form a microcrystalline structure in SBS-modified asphalt, which subsequently improves the anti-fuel of asphalt and its mixtures. This research provides a reference for anti-fuel erosion assessment methods and solutions to improve the anti-fuel erosion of asphalt pavement.

Machine learning models predicts risk of proliferative lupus nephritis.

Objective: This study aims to develop and validate machine learning models to predict proliferative lupus nephritis (PLN) occurrence, offering a reliable diagnostic alternative when renal biopsy is not feasible or safe. Methods: This study retrospectively analyzed clinical and laboratory data from patients diagnosed with SLE and renal involvement who underwent renal biopsy at West China Hospital of Sichuan University between 2011 and 2021. We randomly assigned 70% of the patients to a training cohort and the remaining 30% to a test cohort. Various machine learning models were constructed on the training cohort, including generalized linear models (e.g., logistic regression, least absolute shrinkage and selection operator, ridge regression, and elastic net), support vector machines (linear and radial basis kernel functions), and decision tree models (e.g., classical decision tree, conditional inference tree, and random forest). Diagnostic performance was evaluated using ROC curves, calibration curves, and DCA for both cohorts. Furthermore, different machine learning models were compared to identify key and shared features, aiming to screen for potential PLN diagnostic markers. Results: Involving 1312 LN patients, with 780 PLN/NPLN cases analyzed. They were randomly divided into a training group (547 cases) and a testing group (233 cases). we developed nine machine learning models in the training group. Seven models demonstrated excellent discriminatory abilities in the testing cohort, random forest model showed the highest discriminatory ability (AUC: 0.880, 95% confidence interval(CI): 0.835-0.926). Logistic regression had the best calibration, while random forest exhibited the greatest clinical net benefit. By comparing features across various models, we confirmed the efficacy of traditional indicators like anti-dsDNA antibodies, complement levels, serum creatinine, and urinary red and white blood cells in predicting and distinguishing PLN. Additionally, we uncovered the potential value of previously controversial or underutilized indicators such as serum chloride, neutrophil percentage, serum cystatin C, hematocrit, urinary pH, blood routine red blood cells, and immunoglobulin M in predicting PLN. Conclusion: This study provides a comprehensive perspective on incorporating a broader range of biomarkers for diagnosing and predicting PLN. Additionally, it offers an ideal non-invasive diagnostic tool for SLE patients unable to undergo renal biopsy.

A nomogram to predict the risk of proliferative lupus nephritis in patients with systemic lupus erythematosus involving the kidneys.

Proliferative lupus nephritis (PLN) is a serious organ-threatening manifestation of systemic lupus erythematosus (SLE) that is associated with high mortality and renal failure. Here, we analyzed data from 1287 SLE patients with renal manifestations, including 780 of which were confirmed as proliferative or non-proliferative LN patients by renal biopsy, divided into a training cohort (547 patients) and a validation cohort (233 patients). By applying a least absolute shrinkage and selection operator (LASSO) regression approach combined with multivariate logistic regression analysis to build a nomogram for prediction of PLN that was then assessed by receiver operating characteristic (ROC) curves, calibration curves, and clinical decision curves (DCA) in both the training and validation cohorts. The area under the ROC curve (AUC) of the model in the training cohort was 0.921 (95% confidence interval (CI): 0.895-0.946), the AUC of internal validation in the training cohort was 0.909 and the AUC of external validation was 0.848 (95% CI: 0.796-0.900). The nomogram showed good performance as evaluated using calibration and DCA curves. Taken together, our results indicate that our nomogram that comprises 12 significantly relevant variables could be clinically valuable to prognosticate on the risk of PLN in SLE, so as to improve patient prognoses.

Quantifying the contributions of meteorology, emissions, and transport to ground-level ozone in the Pearl River Delta, China.

Ozone pollution presents a growing air quality threat in urban agglomerations in China. It remains challenge to distinguish the roles of emissions of precursors, chemical production and transportations in shaping the ground-level ozone trends, largely due to complicated interactions among these 3 major processes. This study elucidates the formation factors of ozone pollution and categorizes them into local emissions (anthropogenic and biogenic emissions), transport (precursor transport and direct transport from various regions), and meteorology. Particularly, we attribute meteorology, which affects biogenic emissions and chemical formation as well as transportation, to a perturbation term with fluctuating ranges. The Community Multiscale Air Quality (CMAQ) model was utilized to implement this framework, using the Pearl River Delta region as a case study, to simulate a severe ozone pollution episode in autumn 2019 that affected the entire country. Our findings demonstrate that the average impact of meteorological conditions changed consistently with the variation of ozone pollution levels, indicating that meteorological conditions can exert significant control over the degree of ozone pollution. As the maximum daily 8-hour average (MDA8) ozone concentrations increased from 20 % below to 30 % above the National Ambient Air Quality Standard II, contributions from emissions and precursor transport were enhanced. Concurrently, direct transport within Guangdong province rose from 13.8 % to 22.7 %, underscoring the importance of regional joint prevention and control measures under adverse weather conditions. Regarding biogenic emissions and precursor transport that cannot be directly controlled, we found that their contributions were generally greater in urban areas with high nitrogen oxides (NOx) levels, primarily due to the stronger atmospheric oxidation capacity facilitating ozone formation. Our results indicate that not only local anthropogenic emissions can be controlled in urban areas, but also the impacts of local biogenic emissions and precursor transport can be potentially regulated through reducing atmospheric oxidation capacity.

MiR-34a ameliorates arterial blood flow in rats with lower limb arteriosclerosis obliterans via Sirt1 signaling pathway.

In this study, we investigated the impact of microRNA-34a (miR-34a) on lower limb arteriosclerosis obliterans in rats through the Sirtuin 1 (Sirt1) signaling pathway. Thirty-six Sprague-Dawley rats were divided into normal, model, and miR-34a mimics groups. Rats in the normal group were raised normally, while the model group underwent lower limb arteriosclerosis obliterans induction and received saline injections. The miR-34a mimics group also underwent arteriosclerosis obliterans modeling but received miR-34a mimics injections. Immunohistochemistry revealed significantly increased vascular endothelial growth factor (VEGF) expression in both model and miR-34a mimics groups compared to the normal group, with the miR-34a mimics group showing higher levels. Western blotting indicated elevated Sirt1 protein expression in both non-normal groups, with the miR-34a mimics group exhibiting significantly higher levels. Quantitative polymerase chain reaction (qPCR) demonstrated higher levels of miR-34a, VEGF mRNA, and Sirt1 mRNA in the model group compared to the normal group, but significantly lower levels than the miR-34a mimics group. Enzyme-linked immunosorbent assay (ELISA) showed increased VEGF content in the model group compared to the normal group but decreased compared to the miR-34a mimics group. Hemorrheological detection revealed a reduced PU index in both non-normal groups compared to the normal group, with a significant increase in the miR-34a mimics group compared to the model group. Overall, miR-34a upregulation enhanced VEGF expression in rat blood vessels, ameliorating arterial blood flow in lower limb arteriosclerosis obliterans through the Sirt1 signaling pathway.

Strategies for Achieving Ultra-Long ORR Durability-Rh Activates Interatomic Interactions in Alloys.

The stability of platinum-based alloy catalysts is crucial for the future development of proton exchange membrane fuel cells, considering the potential dissolution of transition metals under complex operating conditions. Here, we report on a Rh-doped Pt3Co alloy that exhibits strong interatomic interactions, thereby enhancing the durability of fuel cells. The Rh-Pt3Co/C catalyst demonstrates exceptional catalytic activity for oxygen reduction reactions (ORR) (1.31 A mgPt -1 at 0.9 V vs. the reversible hydrogen electrode (RHE) and maintaining 92 % of its mass activity after 170,000 potential cycles). Long-term testing has shown direct inhibition of Co dissolution in Rh-Pt3Co/C. Furthermore, tests on proton exchange membrane fuel cells (PEMFC) have shown excellent performance and long-term durability with low Pt loading. After 50,000 cycles, there was no voltage loss at 0.8 A cm-2 for Rh-Pt3Co/C, while Pt3Co/C experienced a loss of 200 mV. Theoretical calculations suggest that introducing transition metal atoms through doping creates a stronger compressive strain, which in turn leads to increased catalytic activity. Additionally, Rh doping increases the energy barrier for Co diffusion in the bulk phase, while also raising the vacancy formation energy of the surface Pt. This ensures the long-term stability of the alloy over the course of the cycle.

ZNF862 induces cytostasis and apoptosis via the p21-RB1 and Bcl-xL-Caspase 3 signaling pathways in human gingival fibroblasts.

OBJECTIVE: This study investigates the effects of ZNF862 on the proliferation and apoptosis of human gingival fibroblasts and their related mechanisms. BACKGROUND: As a major transcription factor family, zinc finger proteins (ZFPs) regulate cell differentiation, growth, and apoptosis through their conserved zinc finger motifs, which allow high flexibility and specificity in gene regulation. In our previous study, ZNF862 mutation was associated with hereditary gingival fibromatosis. Nevertheless, little is known about the biological function of ZNF862. Therefore, this study was aimed to reveal intracellular localization of ZNF862, the influence of ZNF862 on the growth and apoptosis of human gingival fibroblasts (HGFs) and its potential related mechanisms. METHODS: Immunohistochemistry, immunofluorescence staining, and western blotting were performed to determine the intracellular localization of ZNF862 in HGFs. HGFs were divided into three groups: ZNF862 overexpression group, ZNF862 interference group, and the empty vector control group. Then, the effects of ZNF862 on cell proliferation, migration, cell cycle, and apoptosis were evaluated. qRT-PCR and western blotting were performed to further explore the mechanism related to the proliferation and apoptosis of HGFs. RESULTS: ZNF862 was found to be localized in the cytoplasm of HGFs. In vitro experiments revealed that ZNF862 overexpression inhibited HGFs proliferation and migration, induced cell cycle arrest at the G0/G1-phase and apoptosis. Whereas, ZNF862 knockdown promoted HGFs proliferation and migration, accelerated the transition from the G0/G1 phase into the S and G2/M phase and inhibited cell apoptosis. Mechanistically, the effects of ZNF862 on HGFs proliferation and apoptosis were noted to be dependent on inhibiting the cyclin-dependent kinase inhibitor 1A (p21)-retinoblastoma 1 (RB1) signaling pathway and enhancing the B-cell lymphoma-extra-large (Bcl-xL)-Caspase 3 signaling pathway. CONCLUSION: Our results for the first time reveal that ZNF862 is localized in the cytoplasm of HGFs. ZNF862 can inhibit the proliferation of HGFs by inhibiting the p21-RB1 signaling pathway, and it also promotes the apoptosis of HGFs by enhancing the Bcl-xL-Caspase 3 signaling pathway.

SIRT7 promotes the proliferation and migration of anaplastic thyroid cancer cells by regulating the desuccinylation of KIF23.

OBJECTIVE: This study was designed to investigate the regulatory effects of kinesin family member (KIF) 23 on anaplastic thyroid cancer (ATC) cell viability and migration and the underlying mechanism. METHODS: Reverse transcription-quantitative polymerase chain reaction (RT-qPCR) was used to analyze the levels of KIF23 in ATC cells. Besides, the effects of KIF23 and sirtuin (SIRT) 7 on the viability and migration of ATC cells were detected using cell counting kit-8, transwell and wound healing assays. The interaction between SIRT7 and KIF23 was evaluated by co-immunoprecipitation (Co-IP) assay. The succinylation (succ) of KIF23 was analyzed by western blot. RESULTS: The KIF23 expression was upregulated in ATC cells. Silencing of KIF23 suppressed the viability and migration of 8505C and BCPAP cells. The KIF23-succ level was decreased in ATC cells. SIRT7 interacted with KIF23 to inhibit the succinylation of KIF23 at K537 site in human embryonic kidney (HEK)-293T cells. Overexpression of SIRT7 enhanced the protein stability of KIF23 in HEK-293T cells. Besides, overexpression of KIF23 promoted the viability and migration of 8505C and BCPAP cells, which was partly blocked by silenced SIRT7. CONCLUSIONS: SIRT7 promoted the proliferation and migration of ATC cells by regulating the desuccinylation of KIF23.

Can pluripotent/multipotent stem cells reverse Parkinson's disease progression?

Parkinson's disease (PD) is a progressive neurodegenerative disorder characterized by continuous and selective degeneration or death of dopamine neurons in the midbrain, leading to dysfunction of the nigrostriatal neural circuits. Current clinical treatments for PD include drug treatment and surgery, which provide short-term relief of symptoms but are associated with many side effects and cannot reverse the progression of PD. Pluripotent/multipotent stem cells possess a self-renewal capacity and the potential to differentiate into dopaminergic neurons. Transplantation of pluripotent/multipotent stem cells or dopaminergic neurons derived from these cells is a promising strategy for the complete repair of damaged neural circuits in PD. This article reviews and summarizes the current preclinical/clinical treatments for PD, their efficacies, and the advantages/disadvantages of various stem cells, including pluripotent and multipotent stem cells, to provide a detailed overview of how these cells can be applied in the treatment of PD, as well as the challenges and bottlenecks that need to be overcome in future translational studies.

Quantified the influence of different synoptic weather patterns on the transport and local production processes of O3 events in Pearl River Delta, China.

Regional ozone (O3) pollution in the Pearl River Delta (PRD) region has become a topic of discussion in recent years. The occurrence of regional O3 pollution are influenced by local emissions and cross-regional transportation. In this study, we identified the predominant synoptic patterns that were associated with regional O3 pollution from August to November in 2015-2021 using the Lamb-Jenkinson classification technique. All synoptic types were divided into four major categories of NE-type, C-type, S-type and A-type, which accounted for 42 %, 25 %, 18 % and 15 % of the total number of regional O3 pollution days, respectively. The weather conditions for each synoptic pattern were described by using MERRA-2 datasets. Then a rapidly method was established to quantify the contribution of cross-regional processes to high O3 concentration in different synoptic patterns over the PRD through the WRF-Flexpart model. The NE-type weather condition was characterized by a relatively large wind speed with a significant cross-regional transport contribution of 35.8 %. The A-type weather condition had moderate surface wind speed with the stable weather condition, resulting in a lower cross-region transport contribution of 27.7 %. Under controlled by C-type, the stagnant weather condition caused by low-pressure systems on its periphery, would suppress diffusion of O3. As a result, the regional O3 pollution in the PRD were mostly attributed to locally (87.9 %) with minimal cross-regional transport (12.1 %). The S-type weather condition was mainly associated with the West Pacific Subtropical High and the surface equalization pressure field, accompanied by low wind speed. Therefore, the considerable (minor) contribution of local production (cross-regional transport) of 83.3 % (16.7 %) to O3 pollution in the PRD is a consequence of the stagnation weather condition.

[Spatio-temporal Characteristics and Influencing Factors of Ozone Suppression Events Under High Temperature in China].

Temperature is a key meteorological factor affecting ozone formation. In general, a positive correlation is observed between ozone and temperature, that is, ozone concentration increases with the increase in temperature. However, this relationship may change at extremely high temperatures. When the temperature exceeds a threshold value, the ozone concentration tends to decrease, which is referred to as an ozone suppression event. Ozone suppression events lead to greater uncertainties in the prediction of future air quality under climate change. Based on the national air quality monitoring data, reanalysis data, and meteorological observation data, this study used the Z test to systematically analyze the spatio-temporal characteristics of the critical temperature(Tx) and frequency of ozone suppression events in China during the warm season(April to September) from 2013 to 2020 and further analyzed the possible influencing factors for the occurrence of ozone suppression events. The results showed that approximately 18% of the sites in China experienced ozone suppression events in the warm season from 2013 to 2020. The sites with a high frequency of ozone suppression events were mainly distributed in the central and western regions of China, such as Sichuan, Xinjiang, and Shaanxi, with an average frequency of ten times per year. The critical temperature(Tx) ranged from 19.2 to 39.3℃, and the Tx of most sites showed an increasing trend from 2013 to 2020. The high values of Tx were mainly distributed in the central and western regions such as Sichuan, Chongqing, Hunan, and Hubei, whereas the low values of Tx were concentrated in the Qinghai-Tibet Plateau. Contrary to the interannual trend of Tx, the frequency of ozone suppression events decreased significantly in the Beijing-Tianjin-Hebei Region and exhibited a characteristic of "increase-decrease-increase" in the Fenwei Plain, the Yangtze River Delta, and the Chengdu-Chongqing regions. The most significant effect of extreme high temperature on ozone suppresion was found in the Pearl River Delta Region. In addition, ozone precursors(e.g., NO2) and meteorological conditions(wind speed and direction) were possible factors affecting the occurrence of ozone suppression events.

The role of lncRNA in the pathogenesis of chronic obstructive pulmonary disease.

Chronic obstructive pulmonary disease (COPD) is characterized by progressive and irreversible airflow obstruction with abnormal lung function. Because its pathogenesis involves multiple aspects of oxidative stress, immunity and inflammation, apoptosis, airway and lung repair and destruction, the clinical approach to COPD treatment is not further updated. Therefore, it is crucial to discover a new means of COPD diagnosis and treatment. COPD etiology is associated with complex interactions between environmental and genetic determinants. Numerous genes are involved in the pathogenic process of this illness in research samples exposed to hazardous environmental conditions. Among them, Long non-coding RNAs (lncRNAs) have been reported to be involved in the molecular mechanisms of COPD development induced by different environmental exposures and genetic susceptibility encounters, and some potential lncRNA biomarkers have been identified as early diagnostic, disease course determination, and therapeutic targets for COPD. In this review, we summarize the expression profiles of the reported lncRNAs that have been reported in COPD studies related to environmental risk factors such as smoking and air pollution exposure and provided an overview of the roles of those lncRNAs in the pathogenesis of the disease.

Long non-coding RNAs as modulators and therapeutic targets in non-alcoholic fatty liver disease (NAFLD).

Non-alcoholic fatty liver disease (NAFLD) is the most common liver disease in the world, with epidemiological studies indicating a 25% prevalence. NAFLD is considered to be a progressive disease that progresses from simple hepatic steatosis to non-alcoholic steatohepatitis (NASH), then to liver fibrosis, and finally to cirrhosis or hepatocellular carcinoma (HCC). Existing research has mostly elucidated the etiology of NAFLD, yet its particular molecular processes remain uncertain. Long non-coding RNAs (LncRNAs) have been linked in a wide range of biological processes in recent years, with the introduction of microarray and high-throughput sequencing technologies, and previous studies have established their tight relationship with several stages of NAFLD development. Existing studies have shown that lncRNAs can regulate the signaling pathways related to hepatic lipid metabolism, NASH, NASH-related fibrosis and HCC. This review aims to provide a basic overview of NAFLD and lncRNAs, summarize and describe the mechanisms of lncRNAs action involved in the development of NAFLD, and provide an outlook on the future of lncRNAs-based therapy for NAFLD.

A mathematical algorithm to harmonize measurements for thyroid-stimulating hormone between instruments.

BACKGROUND: Thyroid-stimulating hormone (TSH) is measured differently between diagnostic units using different devices, which makes cross-comparisons challenging. Here, we have developed a mathematical algorithm to harmonize TSH measurements between 2 instruments, the Abbott ISR2000 and the Siemens ADVIA Centaur XP. METHODS: Applying the principle of the maximum allowable error between the standard curve and real signal values, the minimum number of comparison samples required for TSH hormone detection was calculated for both instruments. Next, a mathematical algorithm describing the relationship between TSH standard curves from both instruments was established. The algorithm was then tested on sample measurements from both instruments, with signals transformed to Siemens ADVIA Centuar XP-type data. Finally, test results were assessed where the relative error was 1/2 TEa). After algorithmic transformation, the average percentage error was reduced to 7.93% (<1/2 TEa). CONCLUSIONS: Our algorithm enables TSH measurements across different instruments to be comparable, and provides a method to harmonize TSH data between laboratories that utilize different instrumentation.

A new bin size index method for statistical analysis of multimodal datasets from materials characterization.

This paper presents a normalized standard error-based statistical data binning method, termed "bin size index" (BSI), which yields an optimized, objective bin size for constructing a rational histogram to facilitate subsequent deconvolution of multimodal datasets from materials characterization and hence the determination of the underlying probability density functions. Totally ten datasets, including four normally-distributed synthetic ones, three normally-distributed ones on the elasticity of rocks obtained by statistical nanoindentation, and three lognormally-distributed ones on the particle size distributions of flocculated clay suspensions, were used to illustrate the BSI's concepts and algorithms. While results from the synthetic datasets prove the method's accuracy and effectiveness, analyses of other real datasets from materials characterization and measurement further demonstrate its rationale, performance, and applicability to practical problems. The BSI method also enables determination of the number of modes via the comparative evaluation of the errors returned from different trial bin sizes. The accuracy and performance of the BSI method are further compared with other widely used binning methods, and the former yields the highest BSI and smallest normalized standard errors. This new method particularly penalizes the overfitting that tends to yield too many pseudo-modes via normalizing the errors by the number of modes hidden in the datasets, and also eliminates the difficulty in specifying criteria for acceptable values of the fitting errors. The advantages and disadvantages of the new method are also discussed.

Advances in Nanogels for Topical Drug Delivery in Ocular Diseases.

Nanotechnology has accelerated the development of the pharmaceutical and medical technology fields, and nanogels for ocular applications have proven to be a promising therapeutic strategy. Traditional ocular preparations are restricted by the anatomical and physiological barriers of the eye, resulting in a short retention time and low drug bioavailability, which is a significant challenge for physicians, patients, and pharmacists. Nanogels, however, have the ability to encapsulate drugs within three-dimensional crosslinked polymeric networks and, through specific structural designs and distinct methods of preparation, achieve the controlled and sustained delivery of loaded drugs, increasing patient compliance and therapeutic efficiency. In addition, nanogels have higher drug-loading capacity and biocompatibility than other nanocarriers. In this review, the main focus is on the applications of nanogels for ocular diseases, whose preparations and stimuli-responsive behaviors are briefly described. The current comprehension of topical drug delivery will be improved by focusing on the advances of nanogels in typical ocular diseases, including glaucoma, cataracts, dry eye syndrome, and bacterial keratitis, as well as related drug-loaded contact lenses and natural active substances.

Generalized Encapsulations of ZIF-Based Fe-N-C Catalysts with Controllable Nitrogen-Doped Carbon for Significantly-Improved Stability Toward Oxygen Reduction Reaction.

The vigorous development of efficient platinum group metal-free catalysts is considerably important to facilitate the universal application of proton exchange membrane fuel cells. Although nitrogen-coordinated atomic iron intercalated in carbon matrix (Fe-N-C) catalysts exhibit promising catalytic activity, the performance in fuel cells, especially the short lifetime, remains an obstacle. Herein, a highly-active Fe-N-C catalyst with a power density of >1 w cm-2 and prolonged discharge stability with a current density of 357 mA cm-2 after 40 h of constant voltage discharge at 0.7 V in H2 -O2 fuel cells using a controllable and efficient N-C coating strategy is developed. It is clarified that a thicker N-C coating may be more favorable to enhance the stability of Fe-N-C catalysts at the expense of their catalytic activity. The stability enhancement mechanism of the N-C coating strategy is proven to be the synergistic effect of reduced carbon corrosion and iron loss. It is believed that these findings can contribute to the development of Fe-N-C catalysts with high activity and long lifetimes.