Construction and implementation of a laparoscopic skill training course based on a smartphone application and virtual reality.

BACKGROUND: To develop a laparoscopic training course that combines a smartphone application (APP) and virtual reality (VR), and initially evaluate the feasibility and effectiveness of its implementation. METHODS: The Exploring Laparoscopy (Ex-Lap) app was developed to meet training demands. The course was designed by integrating the app with a VR simulator (LapSim®) and animal organ perfusion simulators. From January 2021 to December 2023, 91 participants were enrolled in the study and then divided into 5 separate batches to undergo the first stage of the course. The performance of the participants was evaluated by rating scale, the overall Training and Assessment of Basic Laparoscopic Techniques (TABLT) scores, and pass rates. Statistical analyses were conducted using SPSS 26.0, employing Kruskal-Wallis tests, Chi-squared analysis, and Fisher's exact test, depending on the data type. RESULTS: The Staged Training and Assessment of Laparoscopic Skills (STALS) course was developed, consisting of three stages. The overall pass rates for the first stage across the five batches ranged from 85 to 100%, with no significant difference (P = 0.387). No significant differences were found in the scale scores or TABLT scores for the training tasks among students from different batches (all P > 0.05). CONCLUSIONS: The STALS course is applicable in residency training, demonstrating satisfactory teaching effectiveness and replicability.

The risk factors determined by four machine learning methods for the change of difference of bone mineral density in post-menopausal women after three years follow-up.

The prevalence of osteoporosis has drastically increased recently. It is not only the most frequent but is also a major global public health problem due to its high morbidity. There are many risk factors associated with osteoporosis were identified. However, most studies have used the traditional multiple linear regression (MLR) to explore their relationships. Recently, machine learning (Mach-L) has become a new modality for data analysis because it enables machine to learn from past data or experiences without being explicitly programmed and could capture nonlinear relationships better. These methods have the potential to outperform conventional MLR in disease prediction. In the present study, we enrolled a Chinese post-menopause cohort followed up for 4 years. The difference of T-score (δ-T score) was the dependent variable. Information such as demographic, biochemistry and life styles were the independent variables. Our goals were: (1) Compare the prediction accuracy between Mach-L and traditional MLR for δ-T score. (2) Rank the importance of risk factors (independent variables) for prediction of δ T-score. Totally, there were 1698 postmenopausal women were enrolled from MJ Health Database. Four different Mach-L methods namely, Random forest (RF), eXtreme Gradient Boosting (XGBoost), Naïve Bayes (NB), and stochastic gradient boosting (SGB), to construct predictive models for predicting δ-BMD after four years follow-up. The dataset was then randomly divided into an 80% training dataset for model building and a 20% testing dataset for model testing. A 10-fold cross-validation technique for hyperparameter tuning was used. The model with the lowest root mean square error for the validation dataset was viewed as the best model for each ML method. The averaged metrics of the RF, SGB, NB, and XGBoost models were used to compare the model performance of the benchmark MLR model that used the same training and testing dataset as the Mach-L methods. We defined that the priority demonstrated in each model ranked 1 as the most critical risk factor and 22 as the last selected risk factor. For Pearson correlation, age, education, BMI, HDL-C, and TSH were positively and plasma calcium level, and baseline T-score were negatively correlated with δ-T score. All four Mach-L methods yielded lower prediction errors than the MLR method and were all convincing Mach-L models. From our results, it could be noted that education level is the most important factor for δ-T Score, followed by DBP, smoking, SBP, UA, age, and LDL-C. All four Mach-L outperformed traditional MLR. By using Mach-L, the most important six risk factors were selected which are, from the most important to the least: DBP, SBP, UA, education level, TG and sleeping hour. δ T score was positively related to SBP, education level, UA and TG and negatively related to DBP and sleeping hour in postmenopausal Chinese women.

Synergistically Boosting Li Storage Performance of MnWO4 Nanorods Anode via Carbon Coating and Additives.

Polyanionic structures, (MO4)n-, can be beneficial to the transport of lithium ions by virtue of the open three-dimensional frame structure. However, an unstable interface suppresses the life of the (MO4)n--based anode. In this study, MnWO4@C nanorods with dense nanocavities have been synthesized through a hydrothermal route, followed by a chemical deposition method. As a result, the MnWO4@C anode exhibits better cycle and rate performance than MnWO4 as a Li-ion battery; the capacity is maintained at 718 mAh g-1 at 1000 mA g-1 after 400 cycles because the transport of lithium ions and the contribution of pseudo-capacitance are increased. Generally, benefiting from the carbon shell and electrolyte additive (e.g., FEC), the cycle performance of the MnWO4@C electrode is also effectively improved for lithium storage.

Targeting KIFC1 Promotes Senescence in Soft Tissue Sarcoma via FXR1-Dependent Regulation of MAD2L1 mRNA Stability.

Patients diagnosed with soft tissue sarcoma (STS) often present at intermediate to advanced stages, with inherently limited therapeutic options available. There is an urgent need to identify novel therapeutic targets. In this study, by screening STS data from the Cancer Genome Atlas (TCGA) and Genotype Tissue Expression (GTEx) databases, KIFC1 is identified as a potential biomarker and a promising therapeutic target for STS. Notably, a significant increase in KIFC1 levels, which exhibited a strong correlation with a poor prognosis in STS patients is observed. The findings revealed that knockout of KIFC1 suppressed STS growth both in vitro and in vivo. Furthermore, KIFC1 is found to regulate cellular senescence in STS, which has not been reported before. that targeting KIFC1 induced cellular senescence via interacting with FXR1, an RNA-binding protein is discovered, thereby further stabilizing MAD2L1 mRNA in an m6A-dependent manner. Additionally, the suppression of KIFC1 markedly diminished the growth of patient-derived xenografts (PDX) and triggered senescence. This study provides the first evidence that KIFC1 inhibition induces cellular senescence through MAD2L1, underscoring KIFC1 as a novel prognostic biomarker and a potential therapeutic target for STS.

Impact of metabolic syndrome components on clinical outcomes in hypertriglyceridemia-induced acute pancreatitis.

BACKGROUND: The incidence of hypertriglyceridemia (HTG)-induced acute pancreatitis (AP) is steadily increasing in China, becoming the second leading cause of AP. Clinical complications and outcomes associated with HTG-AP are generally more severe than those seen in AP caused by other etiologies. HTG-AP is closely linked to metabolic dysfunction and frequently coexists with metabolic syndrome or its components. However, the impact of metabolic syndrome components on HTG-AP clinical outcomes remains unclear. AIM: To investigate the impact of metabolic syndrome component burden on clinical outcomes in HTG-AP. METHODS: In this retrospective study of 255 patients diagnosed with HTG-AP at the First Affiliated Hospital of Guangxi Medical University, we collected data on patient demographics, clinical scores, complications, and clinical outcomes. Subsequently, we analyzed the influence of the presence and number of individual metabolic syndrome components, including obesity, hyperglycemia, hypertension, and low high-density lipoprotein cholesterol (HDL-C), on the aforementioned parameters in HTG-AP patients. RESULTS: This study found that metabolic syndrome components were associated with an increased risk of various complications in HTG-AP, with low HDL-C being the most significant risk factor for clinical outcomes. The risk of complications increased with the number of metabolic syndrome components. Adjusted for age and sex, patients with high-component metabolic syndrome had significantly higher risks of renal failure [odds ratio (OR) = 3.02, 95%CI: 1.12-8.11)], SAP (OR = 5.05, 95%CI: 2.04-12.49), and intensive care unit admission (OR = 6.41, 95%CI: 2.42-16.97) compared to those without metabolic syndrome. CONCLUSION: The coexistence of multiple metabolic syndrome components can synergistically worsen the clinical course of HTG-AP, making it crucial to monitor these components for effective disease management.

Electrolyte Engineering with TFA- Anion-Rich Solvation Structure to Construct Highly Stable Zn2+/Na+ Dual-Salt Batteries.

Electrolyte engineering is recognized as an effective technique for high-performance aqueous zinc-ion rechargeable batteries, addressing difficulties such as free water decomposition, zinc anode corrosion, and zinc dendrite growth. Different from traditional strategies in aqueous electrolyte systems, this work focuses on organic electrolytes involving zinc trifluoroacetate hydrate (Zn(TFA)2·xH2O), sodium trifluoroacetate (NaTFA) dual-salt and acetonitrile (AN) solvent, in which trifluoroacetate anions (TFA- anions) have strong affinity toward zinc ions to form anion-rich solvates, thus inducing an inorganic-rich solid electrolyte interphase (SEI) to protect Zn from dendrite growth and side reactions. The Zn anode manifests long-term cycling over 2400 h at a current density of 0.5 mA cm-2 with a high Coulombic efficiency (CE) of 99.75%, showing an areal capacity as high as 5 mAh cm-2. Owing to the high reversibility of the sodium ions intercalation/deintercalation process in Na2MnFe(CN)6, the Zn//Na2MnFe(CN)6 full cells with the dual-salt electrolyte perform much better in terms of capacity retention than a device with Zn(TFA)2/AN electrolyte. This approach may open a new avenue for efficient zinc-ion rechargeable batteries via developing organic electrolytes.

Utilizing diffusion tensor imaging as an image biomarker in exploring the therapeutic efficacy of forniceal deep brain stimulation in a mice model of Alzheimer's disease.

Objective.With prolonged life expectancy, the incidence of memory deficits, especially in Alzheimer's disease (AD), has increased. Although multiple treatments have been evaluated, no promising treatment has been found to date. Deep brain stimulation (DBS) of the fornix area was explored as a possible treatment because the fornix is intimately connected to memory-related areas that are vulnerable in AD; however, a proper imaging biomarker for assessing the therapeutic efficiency of forniceal DBS in AD has not been established.Approach.This study assessed the efficacy and safety of DBS by estimating the optimal intersection volume between the volume of tissue activated and the fornix. Utilizing a gold-electroplating process, the microelectrode's surface area on the neural probe was increased, enhancing charge transfer performance within potential water window limits. Bilateral fornix implantation was conducted in triple-transgenic AD mice (3 × Tg-AD) and wild-type mice (strain: B6129SF1/J), with forniceal DBS administered exclusively to 3 × Tg-AD mice in the DBS-on group. Behavioral tasks, diffusion tensor imaging (DTI), and immunohistochemistry (IHC) were performed in all mice to assess the therapeutic efficacy of forniceal DBS.Main results.The results illustrated that memory deficits and increased anxiety-like behavior in 3 × Tg-AD mice were rescued by forniceal DBS. Furthermore, forniceal DBS positively altered DTI indices, such as increasing fractional anisotropy (FA) and decreasing mean diffusivity (MD), together with reducing microglial cell and astrocyte counts, suggesting a potential causal relationship between revised FA/MD and reduced cell counts in the anterior cingulate cortex, hippocampus, fornix, amygdala, and entorhinal cortex of 3 × Tg-AD mice following forniceal DBS.Significance.The efficacy of forniceal DBS in AD can be indicated by alterations in DTI-based biomarkers reflecting the decreased activation of glial cells, suggesting reduced neural inflammation as evidenced by improvements in memory and anxiety-like behavior.

TET3 is expressed in prostate cancer tumor-associated macrophages and is associated with anti-androgen resistance.

PURPOSE: The aim of this study is to investigate the expression of TET3 in prostate cancer and its effect on the efficacy of anti-androgen therapy (ADT). METHODS: The expression of TET3 in 1965 cases of prostate cancer and 493 cases of normal prostate tissues were analyzed. The CIBERSORT algorithm evaluated the abundance of 22 tumor-infiltrating immune cells in 497 prostate cancers. Subsequently, the expression of TET3 in prostate cancer TAMs was analyzed using 21,292 cells from single-cell RNA sequencing (scRNAseq). In addition, the trajectory of the differentiation process was reconstructed based on pseudotime analysis. Sensitivity prediction of prostate cancers to ADT was evaluated based on GDSC2 and CTRP databases. Another dataset GSE111177 was employed for further analysis. RESULTS: TET3 was over-expressed in prostate cancer, and the expression of TET3 in metastatic prostate cancer was higher than that in non-metastatic prostate cancer. The scRNAseq analysis of prostate cancer showed that TET3 was mainly expressed in TAM. TET3 expressed in early and active TAMs, with the activation of signaling pathways such as energy metabolism, cell communication, and cytokine production. Prostate cancer in TET3 high expression group was more sensitive to ADT drugs such as Bicalutamide and AZD3514, and was also more sensitive to chemotherapy drugs such as Cyclophosphamide, Paclitaxel, and Vincristine, and MAPK pathway inhibitors of Docetaxel and Dabrafenib. CONCLUSIONS: The efficacy of ADT in prostate cancer is related to the expression of TET3 in TAMs, and TET3 may be a potential therapeutic target for coordinating ADT.

Monocarboxylate transporter 4 facilitates Mycobacterium tuberculosis survival through NF-κB p65-mediated interleukin-10 production.

Tuberculosis (TB) is a chronic infectious disease caused by Mycobacterium tuberculosis (Mtb) infection, with the highest single-cause mortality. Monocarboxylate transporter 4 (Mct4) transports intracellular lactate outside, but its role in regulating host immune response against Mtb infection remains unknown. Mct4 expression was upregulated in Mtb-infected macrophages and in patients with TB. Mct4 silencing/deficiency significantly decreased Mtb survival in macrophages and in lungs and spleens of mice, while Mct4 overexpression facilitated Mtb survival in macrophages. Furthermore, Mct4 promoted intracellular lactate transport, nuclear factor κB (NF-κB) p65 activation, and interleukin-10 (IL-10) production upon Mtb infection. Mechanistically, IL-10 silencing and IL-10-neutralizing antibody blocked Mct4 overexpressing increased Mtb survival. Replenishing lactate and NF-κB p65 inhibitor JSH23 treatment could inhibit Mct4 overexpressing increased NF-κB p65 activation, IL-10 production, and Mtb survival in macrophages. This study demonstrates that Mct4 promotes Mtb survival through restricting intracellular lactate accumulation to promote NF-κB p65-mediated IL-10 production and suggests Mct4-NF-κB p65-IL-10 axis a potential target for TB treatment.

Nonlocal meta-lens with Huygens' bound states in the continuum.

Meta-lenses composed of artificial meta-atoms have stimulated substantial interest due to their compact and flexible wavefront shaping capabilities, outperforming bulk optical devices. The operating bandwidth is a critical factor determining the meta-lens' performance across various wavelengths. Meta-lenses that operate in a narrowband manner relying on nonlocal effects can effectively reduce disturbance and crosstalk from non-resonant wavelengths, making them well-suitable for specialized applications such as nonlinear generation and augmented reality/virtual reality display. However, nonlocal meta-lenses require striking a balance between local phase manipulation and nonlocal resonance excitation, which involves trade-offs among factors like quality-factor, efficiency, manipulation dimensions, and footprint. In this work, we experimentally demonstrate the nonlocal meta-lens featuring Huygens' bound states in the continuum (BICs) and its near-infrared imaging application. All-dielectric integrated-resonant unit is particularly optimized to efficiently induce both the quasi-BIC and generalized Kerker effect, while ensuring the rotation-angle robustness for generating geometric phase. The experimental results show that the single-layer nonlocal Huygens' meta-lens possesses a high quality-factor of 104 and achieves a transmission polarization conversion efficiency of 55%, exceeding the theoretical limit of 25%. The wavelength-selective two-dimensional focusing and imaging are demonstrated as well. This work will pave the way for efficient nonlocal wavefront shaping and meta-devices.

From Local to Nonlocal High-Q Plasmonic Metasurfaces.

The physics of bound states in the continuum (BICs) allows the design and demonstration of optical resonant structures with large values of the quality factor (Q factor) by employing dielectric structures with low losses. However, BIC is a general wave phenomenon that should be observed in many systems, including the metal-dielectric structures supporting surface plasmon polaritons where optical resonances are hindered by losses. Here we suggest and develop a comprehensive strategy to achieve high-Q resonances in plasmonic metasurfaces by effectively tailoring the resonant modes from local to nonlocal regimes, thus transitioning from quasi-isolated localized resonances to extended resonant modes involving strong interaction among neighboring structure metaunits.

Evaluation of the potential horizontal gene transfer ability during chicken manure and pig manure composting.

Resistance genes have been identified as emerging pollutants due to their ability to rapidly spread in the environment through horizontal gene transfer (HGT). Microbial community serves as the pivotal factor influencing the frequency of HGT during manure composting. However, the characteristics of HGT in microbial community from different types of manure were unclear. Therefore, this study aimed to evaluate the potential risk of HGT in bacterial community through the co-composting of chicken manure and pig manure in different proportions. The experimental results showed that the abundance of sulfonamide antibiotic resistance genes and integrase genes was higher during pig manure composting than those during chicken manure composting. In addition, the addition of pig manure also increased resistance genes abundance during chicken manure composting. These results suggested that the potential HGT risk was greater during pig manure composting. Furthermore, microbial analysis of co-composting suggested that bacterial community of pig manure was more competitive and adaptable than that of chicken manure. Ultimately, statistical analysis indicated that compared to chicken manure composting, the potential ability of HGT was greater during pig manure composting. This study provided the vital theoretical support and scientific guidance for mitigating the HGT risk during manure composting.

Correlation between neuropsychiatric systemic lupus erythematosus and immunological markers: a real-world retrospective study.

OBJECTIVES: This study aimed to investigate disparities in clinical profiles and autoantibody patterns between patients with and without neuropsychiatric systemic lupus erythematosus (NPSLE) in a cohort and to identify risk factors associated with NPSLE in the Chinese population. METHODS: SLE patients were retrospectively reviewed from two tertiary hospitals. The relationships between NPSLE and immunological biomarkers were explored. RESULTS: Among the 945 SLE patients, 75 (7.94%) were diagnosed with NPSLE. The most prevalent NP manifestations involved cognitive disorder (30.67%), headache (26.67%), seizure disorder (26.67%), and psychosis (26.67%).We observed significant associations between psychosis and anti-ß2GPI antibodies (F = 6.092, p = 0.015), polyneuropathy and anti-Scl70 antibodies (F = 20.161, p < 0.001), demyelinating syndrome and anti-cardiolipin antibodies (F = 6.637, p = 0.011), myasthenia gravis and anti-RNP (F = 5.864, p = 0.017), and anti-Smith antibodies (F = 5.096, p = 0.026). Multivariate logistics analysis showed that anti-prothrombin (aPT) IgM antibodies (OR = 10.985, CI 1.279-94.343, p = 0.029), age (OR = 1.169, CI 1.032-1.325, p = 0.014), and serum creatinine (SCr) (OR = 1.014, CI 1.003-1.025, p = 0.009) were independent risk factors of NPSLE, while anti-Sjogren syndrome antigen B (SSB) antibodies (OR 0.023, CI 0.002-0.622, p = 0.023) and high complement C3 (OR = 0.001, CI 0-0.045, p < 0.001) indicated reduced risk of NPSLE. CONCLUSION: Various neuropsychiatric manifestations in SLE were found to be correlated with specific autoantibodies. Independent risk factors for NPSLE included aPT IgM antibodies, age, and elevated serum creatinine, while the absence of anti-SSB antibodies and low complement C3 levels were associated with increased risk. KEY POINTS: •Significant associations were found between specific autoantibodies and neuropsychiatric symptoms, shedding light on potential biomarkers for predicting and understanding NPSLE. •The study identifies independent risk factors for NPSLE in the Chinese population, including the presence of anti-prothrombin IgM antibodies, older age, elevated serum creatinine, and lower complement C3 levels.

The Quantitative Evaluation of Automatic Segmentation in Lumbar Magnetic Resonance Images.

OBJECTIVE: This study aims to overcome challenges in lumbar spine imaging, particularly lumbar spinal stenosis, by developing an automated segmentation model using advanced techniques. Traditional manual measurement and lesion detection methods are limited by subjectivity and inefficiency. The objective is to create an accurate and automated segmentation model that identifies anatomical structures in lumbar spine magnetic resonance imaging scans. METHODS: Leveraging a dataset of 539 lumbar spinal stenosis patients, the study utilizes the residual U-Net for semantic segmentation in sagittal and axial lumbar spine magnetic resonance images. The model, trained to recognize specific tissue categories, employs a geometry algorithm for anatomical structure quantification. Validation metrics, like Intersection over Union (IOU) and Dice coefficients, validate the residual U-Net's segmentation accuracy. A novel rotation matrix approach is introduced for detecting bulging discs, assessing dural sac compression, and measuring yellow ligament thickness. RESULTS: The residual U-Net achieves high precision in segmenting lumbar spine structures, with mean IOU values ranging from 0.82 to 0.93 across various tissue categories and views. The automated quantification system provides measurements for intervertebral disc dimensions, dural sac diameter, yellow ligament thickness, and disc hydration. Consistency between training and testing datasets assures the robustness of automated measurements. CONCLUSION: Automated lumbar spine segmentation with residual U-Net and deep learning exhibits high precision in identifying anatomical structures, facilitating efficient quantification in lumbar spinal stenosis cases. The introduction of a rotation matrix enhances lesion detection, promising improved diagnostic accuracy, and supporting treatment decisions for lumbar spinal stenosis patients.

The expected changes with different periods of home-based resistance exercise in patients with chronic kidney disease.

BACKGROUND: The comprehensive impact of prolonged home-based resistance training on individuals grappling with chronic kidney disease (CKD) have yet to be fully elucidated. This study aimed to explore the outcomes of varying exercise durations on physical performance, nutritional status, and kidney function within this specific population, encompassing patients undergoing dialysis and those affected by severe sarcopenia. METHODS: This was a 1-year observational double cohort study following a 52-week longitudinal design, we enrolled 101 adult CKD outpatients. These participants were divided into two groups: the continuous group, comprising individuals who consistently exercised for over 6 months, and the interrupted group, which included those who did not sustain regular exercise for the same duration. The exercise regimen involved resistance exercises conducted at least 3 to 5 days per week, involving activities like lifting dumbbells and executing weighted wall squats. Physical activity assessments and biochemical blood tests were conducted at weeks 0, 4, 16, 28, 40, and 52 for all participants. RESULTS: The continuous exercise group exhibited better handgrip strength and sit-to-stand movement compared to the interrupted group. Their estimated glomerular filtration rate stayed steady while the interrupted group was declined. Additionally, those who exercised consistently had better metabolism: higher carbon dioxide levels, increased albumin, better nutritional scores, and lower levels of blood urea nitrogen, creatinine, fasting blood glucose, and body weight. Subsequent adjustments for potential confounding factors continued to show improved physical performance and kidney function over time. CONCLUSION: Our findings indicate the advantageous impact of extended resistance exercise training on overall health of CKD patients, even those on dialysis or with severe sarcopenia. Dedication to this exercise routine could improve kidney function, metabolism, and physical abilities in these patients.

Effects of KRAS, STK11, KEAP1, and TP53 mutations on the clinical outcomes of immune checkpoint inhibitors among patients with lung adenocarcinoma.

BACKGROUND: This study aimed to identify the associations between individual KRAS, STK11, KEAP1, or TP53 mutations, as well as the comutation status of these genes, and the tumor mutation burden (TMB) with clinical outcomes of lung adenocarcinoma patients treated with immune checkpoint inhibitors (ICIs). METHODS: We collected data from patients with lung adenocarcinoma treated with ICIs from the Center for Cancer Genomics and Advanced Therapeutics (C-CAT) database between June 2019 and August 2023. The main endpoints were the treatment response and overall survival (OS). RESULTS: Among 343 patients with lung adenocarcinoma, 61 (18%), 69 (20%), 41 (12%), and 222 (65%) patients had KRAS, STK11, KEAP1, and TP53 mutations, respectively. An overall objective response was observed in 94 of 338 patients (28%), including 2 (1%) who achieved a complete response and 92 (27%) who achieved a partial response. Patients with STK11, KEAP1, or TP53 mutations had a significantly greater TMB (P<0.001). According to the univariate analysis, the treatment response was significantly correlated with TP53 mutation in both the general (P = 0.041) and KRAS wild-type (P = 0.009) populations. KEAP1 and TP53 mutations were associated with worse OS among assessable patients (hazard ratio (HR) = 2.027, P = 0.002; HR = 1.673, P = 0.007, respectively) and among patients without KRAS mutations (HR = 1.897, P = 0.012; HR = 1.908, P = 0.004, respectively). According to the multivariate analysis, KEAP1 (HR = 1.890, P = 0.008) and TP53 (HR = 1.735, P = 0.011) mutations were found to be independent factors for OS. CONCLUSIONS: STK11, KEAP1, and TP53 mutations are significantly associated with a high TMB. TP53 mutation could affect the treatment response to some degree, and both KEAP1 and TP53 mutations resulted in inferior OS in the general patient population and in those with KRAS-wild-type lung adenocarcinoma, indicating that KEAP1 and TP53 mutations might act as prognostic factors for ICI treatment in lung adenocarcinoma patients.

Topical Clonidine Accelerates Cutaneous Wound Healing in Diabetic Rats by Regulating the Expression of Related Cytokine Signaling.

Based on the analgesic and anti-inflammatory effects of clonidine in previous studies, we hypothesized that clonidine could accelerate wound healing in rats by regulating the expression of related cytokines. In this study, the wound healing effect of clonidine was evaluated using an excision wound model in diabetic rats and a HaCaT cell model. The wounds were treated daily with topical clonidine. The results analyzed by ImageJ2 software show that the wounds of the rats that were treated with 15 ng/mL clonidine recovered faster, and the wound size was also significantly reduced compared to the control group. Western blot assays determined that clonidine induced an increase in the expression of vascular growth factors, namely, Ang-1, Ang-2, and VEGF. Moreover, clonidine demonstrated a rescuing effect on JAK2 within the JAK/STAT pathway by inhibiting SOCS3 expression, leading to decreased SOCS3 levels and increased expression of JAK2 and phospho-STAT3. Histopathological analysis revealed that clonidine promoted complete epithelial repair and minimized inflammation in skin tissue. Additionally, clonidine stimulated HaCaT cell proliferation in vitro and enhanced cellular energy levels in the presence of AGEs. In conclusion, clonidine promoted vascular growth and wound healing by stimulating the expression of cytokines that are beneficial for wound healing.

Visualising cancer in 3D: 3-Dimensional Tissue Imaging for management of cutaneous basal cell carcinoma.

Surgical management of basal cell carcinoma (BCC) typically involves surgical excision with post-operative margin assessment using the bread-loafing technique; or gold-standard Mohs micrographic surgery (MMS), where margins are iteratively examined for residual cancer after tumour removal, with additional excisions performed upon detecting residual tumour at margins. There is limited sampling of resection margins with bread loafing, with detection of positive margins 44% of the time using 2 mm intervals. To resolve this, we have developed three-dimensional (3D) Tissue Imaging for: (1) complete examination of cancer margins and (2) detection of tumour proximity to nerves and blood vessels. 3D Tissue optical clearing with a light sheet imaging protocol was developed for margin assessment in two datasets assessed by two independent evaluators: (1) 48 samples from 29 patients with varied BCC subtypes, sizes and pigmentation levels; (2) 32 samples with matching Mohs' surgeon reading of tumour margins using two-dimensional haematoxylin & eosin-stained sections. The 3D Tissue Imaging protocol permits a complete examination of deeper and peripheral margins. Two independent evaluators achieved negative predictive values of 92.3% and 88.24% with 3D Tissue Imaging. Images obtained from 3D Tissue Imaging recapitulates histological features of BCC, such as nuclear crowding, palisading and retraction clefting and provides a 3D context for recognising normal skin adnexal structures. Concurrent immunofluorescence labelling of nerves and blood vessels allows visualisation of structures closer to tumour-positive regions, which may have a higher risk for neural and vascular infiltration. Together, this method provides more information in a 3D spatial context, enabling better cancer management by clinicians.

Glycine-Modified Co-MOF Pervaporation Membrane to Enhance Water Transporting.

Cobalt-based metal-organic frameworks (Co-MOFs) with a two-dimensional layered morphology have received increasing attention for pervaporation due to their stability and hydrophilic properties. Using amino glycine (Gly) as a cross-linking agent, the Co-MOF ultrathin two-dimensional membrane doped with organic filler sodium alginate (SA) with the "brick-mixed-sand" structure was proposed. Polyacrylonitrile (PAN) was selected as the support layer of the hybrid membrane. The introduction of Gly efficiently solved the nanomaterial stacking problem and controllably adjusted the interlayer spacing between the nanosheets, which demonstrated good performance for ethanol dehydration. The results of this experimental research showed that the total flux of alcohol/water (9:1) separation by Gly-Co-MOF-SA/PAN hybrid membranes reached 1902 g m-2 h-1, which was 67% higher than that of the pure SA membranes. The "brick-mixed-sand" lamellar dense morphology of Gly-Co-MOF not only enhances membrane hydrophilicity but also provides effective channels for the rapid transport of water, which is expected to be used for the dehydration of organic solvents.