Carbohydrate-based block copolymers with sub-10 nm face-centered cubic nanostructures for low-power-consuming and ultraviolet light-triggered synaptic phototransistors.

Addressing environmental concerns and producing sustainable and environmentally friendly electronic devices with low power consumption poses a significant challenge. This study introduces phototransistor devices employing morphologically controlled block copolymers based on maltotriose, maltoheptaose, and ß-cyclodextrin as polymer electrets. Ordered self-assembled morphologies can be achieved by utilizing microwave radiation for rapid annealing (within 5 s) with optimized annealing conditions. Herein, face-centered cubic (FCC), vertical, and mixed cylindrical nanostructures are reported. The resulting well-defined morphologies play a pivotal role in enhancing the electron-trapping capability of the block copolymers and facilitating charge carrier transport between the electret and semiconducting layers. Consequently, the phototransistor memory manifests exceptional performance, featuring stability and endurance. Intriguingly, the cavity of ß-cyclodextrin provides a stable environment for the trapped charges, leading to a larger memory window than other block copolymers. On the other hand, a device consisting of MT-b-PS exhibited superior current contrast exceeding 106 even under a low drain voltage of -1 V, attributed to sub-10 nm FCC nanostructures. Furthermore, this phototransistor device successfully emulated the synaptic functions of sensing, learning, and short- and long-term memory in the human brain, along with a low energy consumption of 0.312 fJ. Hence, this report opens the pathways for developing promising bio-based electronic devices.

[A comprehensive undergraduate experiment: preparation and chromatographic evaluation of a core-shell stationary phase based on a covalent organic framework].

Continuously promoting new curriculum standards is a key aim of the Ministry of Education of China. With this in mind, this paper introduces a comprehensive teaching experiment for undergraduate instrumental analysis courses that aims to improve students' material-preparation and instrumental-analysis skills through practice. Herein, a covalent organic framework-based core-shell stationary phase material (SiO2@COFTTA-DHTA) is prepared via a one-pot method and characterized in detail, after which its chromatographic properties are evaluated by high performance liquid chromatography (HPLC). The experimental process includes material synthesis and characterization, as well as studying the chromatographic-retention behavior and chromatographic-separation performance of the material. By the combining theoretical science and experimental teaching, this experiment not only deepens students' understanding of the properties of functional materials and their applications, but also improves their experimental-design and critical-thinking skills. This experiment not only cultivates students' interests in scientific research, but also exercises their experimental, operational, innovative-thinking, and practical abilities, while concurrently enhancing their sense of social responsibility and historical mission, thereby delivering the all-round educational goals of experimental teaching.

[Application of single-sperm sequencing in resolving the carrier status of preimplantation genetic testing for chromosomal structural rearrangements in Robertsonian translocations].

OBJECTIVE: To investigate the application value of single-sperm sequencing in resolving the carrier status of preimplantation genetic testing (PGT) for chromosomal structural rearrangements in Robertsonian translocations. METHODS: Haplotypes were constructed by single-sperm isolation combined with single-sperm sequencing for a patient with 45, XY, der(13; 14)(q10; q10). Twenty single-sperm samples were isolated by mechanical braking and subjected to whole-genome amplification (WGA), and then the Asian Screening Array (ASA) gene chip was used to detect the 183 708 single nucleotide polymorphisms (SNP) of the WGA products. The single sperm associated with the translocation that could be used as haplotype inference was detected by copy number variation (CNV) sequencing, and the chromosomal haplotypes with normal and Robertsonian translocations were inferred. Three biopsy samples of embryonic trophoblast cells were used as the objects. After whole-genome amplification, high-throughput sequencing was employed to determine the status of the translocation chromosome carried by the embryos. The available blastocysts were selected for transfer, and the amniotic fluid samples were taken at 18 weeks of gestation to confirm whether the fetus carried the pathogenic mutation. RESULTS: A total of 6 037 SNP sites were screened by single-sperm sequencing, and 30 sites selected to distinguish normal and translocation haplotypes. Preimplantation haplotype analysis showed that all the three embryos were euploids without Robertsonian translocation chromosome. Genetic testing of amniotic fluid in the second trimester confirmed that the karyotype of the fetus was 46, XN, carrying no Robertsonian translocation chromosome. CONCLUSION: For male carriers of Robertsonian translocation, single sperm sequencing can be used to screen SNP sites to construct haplotypes for distinguishing normal and Robertsonian translocation embryos, and to provide a basis for embryo selection by preimplantation chromosomal structural genetic testing.

A Study of MgZnO Thin Film for Hydrogen Sensing Application.

This research introduces a hydrogen sensor made from a thin film of magnesium zinc oxide (MgZnO) deposited using a technique called radiofrequency co-sputtering (RF co-sputtering). Separate magnesium oxide (MgO) and zinc oxide (ZnO) targets were used to deposit the MgZnO film, experimenting with different deposition times and power levels. The sensor performed best (reaching a sensing response of 2.46) when exposed to hydrogen at a concentration of 1000 parts per million (ppm). This peak performance occurred with a MgZnO film thickness of 432 nanometers (nm) at a temperature of 300 °C. Initially, the sensor's responsiveness increased as the film thickness grew. This is because thicker films tend to have more oxygen vacancies, which are imperfections that play a role in the sensor's function. However, further increases in film thickness beyond the optimal point harmed performance. This is attributed to the growth of grains within the film, which hindered its effectiveness. X-ray diffraction (XRD) and field-emission scanning electron microscopy (FE-SEM) were employed to thoroughly characterize the quality of the MgZnO thin film. These techniques provided valuable insights into the film's crystal structure and morphology, crucial factors influencing its performance as a hydrogen sensor.

Deep learning based approach: automated gingival inflammation grading model using gingival removal strategy.

Gingival inflammation grade serves as a well-established index in periodontitis. The aim of this study was to develop a deep learning network utilizing a novel feature extraction method for the automatic assessment of gingival inflammation. T-distributed Stochastic Neighbor Embedding (t-SNE) was utilized for dimensionality reduction. A convolutional neural network (CNN) model based on DenseNet was developed for the identification and evaluation of gingival inflammation. To enhance the performance of the deep learning (DL) model, a novel teeth removal algorithm was implemented. Additionally, a Grad-CAM + + encoder was applied to generate heatmaps for computer visual attention analysis. The mean Intersection over Union (MIoU) for the identification of gingivitis was 0.727 ± 0.117. The accuracy rates for the five inflammatory degrees were 77.09%, 77.25%, 74.38%, 73.68% and 79.22%. The Area Under the Receiver Operating Characteristic (AUROC) values were 0.83, 0.80, 0.81, 0.81 and 0.84, respectively. The attention ratio towards gingival tissue increased from 37.73% to 62.20%, and within 8 mm of the gingival margin, it rose from 21.11% to 38.23%. On the gingiva, the overall attention ratio increased from 51.82% to 78.21%. The proposed DL model with novel feature extraction method provides high accuracy and sensitivity for identifying and grading gingival inflammation.

Stabilization of polyacrylonitrile-based fiber with a quasi-traveling microwave applicator.

This study introduces a novel microwave applicator and optimized processing conditions to enhance the stability of Polyacrylonitrile (PAN)-based precursor fiber (PF). The innovative microwave applicator facilitates the propagation of the electromagnetic (EM) field akin to a quasi-traveling wave, thus circumventing standing wave nodes. This ensures a uniform thermal distribution and broadens the heating zone. Utilizing this applicator, the PF undergoes thermal stabilization in a streamlined two-step process, completing in just 13 min, a significant improvement over the conventional 90-min process. This not only saves manufacturing time, promoting energy efficient manufacturing but also aligns with the global trend towards green energy and lightweight carbon fiber-reinforced polymer matrix composites, potentially catalyzing rapid economic growth. Fiber characterization through Raman spectroscopy (RS), X-ray diffraction (XRD), differential scanning calorimetry (DSC), and complex permittivity measurements reveals that the microwave-processed fiber meets the standard of commercial stabilization fiber (SF).

Ultralow-Energy-Consumption Photosynaptic Transistor Utilizing Conjugated Polymers/Perovskite Quantum Dots Nanocomposites With Ligand Density Optimization.

The photosynaptic transistor stands as a promising contender for overcoming the von Neumann bottleneck in the realm of photo-communication. In this context, photonic synaptic transistors is developed through a straightforward solution process, employing an organic semiconducting polymer with pendant-naphthalene-containing side chains (PDPPNA) in combination with ligand-density-engineered CsPbBr3 perovskite quantum dots (PQDs). This fabrication approach allows the devices to emulate fundamental synaptic behaviors, encompassing excitatory postsynaptic current, paired-pulse facilitation, the transition from short-to-long-term memory, and the concept of "learning experience." Notably, the phototransistor, incorporating the blend of the PDPPNA and CsPbBr3 PQDs washed with ethyl acetate, achieved an exceptional memory ratio of 104. Simultaneously, the same device exhibited an impressive paired-pulse facilitation ratio of 223% at a moderate operating voltage of -4 V and an extraordinarily low energy consumption of 0.215 aJ at an ultralow operating voltage of -0.1 mV. Consequently, these low-voltage synaptic devices, constructed with a pendant side-chain engineering of organic semiconductors and a ligand density engineering of PQDs through a simple fabrication process, exhibit substantial potential for replicating the visual memory capabilities of the human brain.

Neutrophils Recruited by NKX2-1 Suppression via Activation of CXCLs/CXCR2 Axis Promote Lung Adenocarcinoma Progression.

NK2 Homeobox 1 (NKX2-1) is a well-characterized pathological marker that delineates lung adenocarcinoma (LUAD) progression. The advancement of LUAD is influenced by the immune tumor microenvironment through paracrine signaling. However, the involvement of NKX2-1 in modeling the tumor immune microenvironment is still unclear. Here, the downregulation of NKX2-1 is observed in high-grade LUAD. Meanwhile, single-cell RNA sequencing and Visium in situ capturing profiling revealed the recruitment and infiltration of neutrophils in orthotopic syngeneic tumors exhibiting strong cell-cell communication through the activation of CXCLs/CXCR2 signaling. The depletion of NKX2-1 triggered the expression and secretion of CXCL1, CXCL2, CXCL3, and CXCL5 in LUAD cells. Chemokine secretion is analyzed by chemokine array and validated by qRT-PCR. ATAC-seq revealed the restrictive regulation of NKX2-1 on the promoters of CXCL1, CXCL2, and CXCL5 genes. This phenomenon led to increased tumor growth, and conversely, tumor growth decreased when inhibited by the CXCR2 antagonist SB225002. This study unveils how NKX2-1 modulates the infiltration of tumor-promoting neutrophils by inhibiting CXCLs/CXCR2-dependent mechanisms. Hence, targeting CXCR2 in NKX2-1-low tumors is a potential antitumor therapy that may improve LUAD patient outcomes.

Risk of hepatocellular carcinoma occurrence after antiviral therapy for patients with chronic hepatitis C Infection: a systematic review and meta-analysis.

BACKGROUND AND AIMS: The risk of hepatocellular carcinoma (HCC) occurrence following antiviral therapy in patients with chronic hepatitis C (CHC) remains unclear. The current study aims to compare: (1) the HCC occurrence rate following sustained virological response (SVR) versus non-response (NR); (2) the HCC occurrence rate following direct-acting antiviral (DAA) therapy versus interferon (IFN)-based therapy, and (3) the HCC occurrence rate in SVR patients with or without cirrhosis. METHODS: A search was performed for articles published between January 2017 and July 2022. Studies were included if they assessed HCC occurrence rate in CHC patients following anti-HCV therapy. Random effects meta-analysis was used to synthesize the results from individual studies. RESULTS: A total of 23 studies including 29,395 patients (IFN-based = 6, DAA = 17; prospective = 10, retrospective = 13) were included in the review. HCC occurrence was significantly lower in CHC with SVR (1.54 per 100 person-years (py, 95% CI 1.52, 1.57) than those in non-responders (7.80 py, 95% CI 7.61, 7.99). Stratified by HCV treatment regimens, HCC occurrence following SVR was 1.17 per 100 py (95% CI 1.11, 1.22) and 1.60 per 100 py (95% CI 1.58, 1.63) in IFN- and DAA treatment-based studies. HCC occurrence was 0.85 per 100 py (95% CI 0.85, 0.86) in the non-cirrhosis population and rose to 2.47 per 100 py (95% CI 2.42, 2.52) in the cirrhosis population. Further meta-regression analysis showed that treatment types were not associated with a higher HCC occurrence rate, while cirrhosis status was an important factor of HCC occurrence rate. CONCLUSION: HCC occurrence was significantly lower in the SVR population than in the NR population. HCC risk following SVR occurred three times more frequently in patients with cirrhosis than patients without cirrhosis. However, we found no significant difference in HCC occurrence risk following SVR between DAA and IFN therapies. CLINICAL TRIAL NUMBER: CRD42023473033.

Efficient detection of driver fatigue state based on all-weather illumination scenarios.

Among the causes of the annually traffic accidents, driving fatigue is the main culprit. In consequence, it is of great practical significance to carry out the research of driving fatigue detection and early warning system. However, there are still two problems in the latest methods of driving fatigue detection: one is that a single information cannot precisely reflect the actual state of the driver in different fatigue phases, another one is the detection effect is not very well or even difficult to detect under abnormal illumination. In this paper, the multi-task cascaded convolutional networks (MTCNN) and infrared-based remote photo-plethysmography (rPPG) theory are used to extract the driver's facial and physiological information, and the multi-modal specific fatigue information is deeply excavated, and the multi-modal feature fusion model is constructed to comprehensively analyze the driver's fatigue variation tendency. Aiming at the matter of low detection accuracy under abnormal illumination, the multi-modal features extracted from visible light images and infrared images are fused by multi-loss reconstruction (MLR) module, and the driving fatigue detection module is established which is based on Bi-LSTM model by utilizing fatigue timing. The experiments were validated under all-weather illumination scenarios and were carried out on the datasets NTHU-DDD, UTA-RLDDD and FAHD. The results show that the multi-modal driving fatigue detection model has better performance than the single-modal model, and the accuracy is improved by 8.1%. In the abnormal illumination such as strong and weak light, the accuracy of the method can reach 91.7% at the highest and 83.6% at the lowest. Meanwhile, in the normal illumination, it can reach 93.2%.

Attention mechanism-enhanced graph convolutional neural network for unbalanced lithology identification.

In this study, we propose a novel method for identifying lithology using an attention mechanism-enhanced graph convolutional neural network (AGCN). The aim of this method is to address the limitations of traditional approaches that evaluate unbalanced lithology by improving the identification of thin layers and small samples, while providing reliable data support for reservoir evaluation. To achieve this goal, we begin by using Principal Component Analysis (PCA) with maximum and minimum distance clustering (Max-min-distance) to correct the logging curves, which compensates for the low resolution of thin layers and enhances the accuracy of stratigraphic representation. Subsequently, we transform the logging data into graph-structured data by connecting distance similarity points and feature similarity points of the logging samples. We then use the graph convolutional network (GCN) to identify lithology, leveraging both labeled and unlabeled data to enhance the ability to identify lithology in small sample datasets. Additionally, our model incorporates a channel and spatial attention mechanism that assigns weights to the graph structure during lithology identification, improving the model's capability to discern differences across samples. To evaluate the performance of our model, we constructed a lithology dataset comprising five wells and conducted experiments. The results indicate that our approach achieves a maximum accuracy of 97.67%, surpassing the performance of a singlestructure model in lithology identification. In conclusion, our proposed method provides a promising and effective approach for unbalanced lithology identification, significantly improving accuracy levels.

The effect of different times of day for exercise on blood glucose fluctuations.

AIMS: This study aims to explore blood glucose variations before and after short-term intensive exercise in the morning or afternoon of a day and the trend of blood glucose fluctuations during exercise in patients with T2DM (type 2 diabetes, T2DM). METHODS: Blood glucose variations of Fouty during morning exercise 8:00-12:00 hours and twenty during afternoon exercise 14:30-18:30 hours). Patients with T2DM discharged from the hospital were analyzed retrospectively, with the baseline data checked through the medical record system before intervention. We were asked to perform seven times of treadmill aerobic exercise, which lasted for 30 minutes with incremental intensity for each time, for two weeks under the supervision of the Continuous Glucose Monitor (CGM) and the heart rate armband. The exercise intensity has been adjusted by the clinicians and specialist nurses from the Department of Diabetes Mellitus according to the blood glucose levels and heart rate curves during exercise; data including the height, weight, body mass index (BMI), waist-to-hip ratio, fasting blood glucose, glycosylated hemoglobin, in-exercise CGM-measured blood glucose value/min, and after-exercise fingertip blood glucose value of patients with T2DM were collected after the intensive exercise (2 weeks). SPSS 22.0 and GraphPad Prism 7 were adopted for statistical analysis using the T-test and ANOVA. RESULT: No difference was observed in the baseline data between the morning and afternoon exercise groups before intervention; compared to the morning exercise group, the fasting C-peptide value (2.15±0.97 vs. 1.53±0.46) in the afternoon exercise group was higher than that in the morning exercise group, with a superior (p=0.029) effect after two weeks of intervention, exhibiting a significant difference in the results. According to the results of repeated variance ANOVA analysis, the time for the appearance of significant improvement in blood glucose in the afternoon exercise group was 5 minutes earlier (11th minute vs 1 minute)than that in the morning exercise group (15th minute vs 1 min); significant differences were observed in both time (p=0.048 vs p<0.01) between the two groups on exercise days, as revealed by the results of bivariate ANOVA; in comparison to the morning exercise group (7.42±1.68), there was a significant difference (p=0.049)in the mean blood glucose between the two groups 25 min after patients with T2DM in the afternoon exercise group (6.25±1.53) started to exercise; in addition, a significant statistical difference (p=0.021) was revealed in the CGM-measured hourly the mean blood glucose on exercise days between the morning(8.18±1.88) and afternoon exercise (6.75±1.40)groups at 4:00 pm in week one and two w. CONCLUSIONS: Glycaemic improvement in the short-term intensive afternoon exercise group may be superior to that of the morning exercise group, which may be related to greater fasting C-peptide secretion and longer effective exercise duration. The time to exercise is a factor affecting blood glucose variations during exercise. However, significant variations in the level of blood glucose during exercise must be further observed through exercise intervention over a more extended period.

Association between biological aging and periodontitis using NHANES 2009-2014 and mendelian randomization.

Aging is a recognized risk factor for periodontitis, while biological aging could provide more accurate insights into an individual's functional status. This study aimed to investigate the potential association between biological aging and periodontitis. Epidemiological data from 9803 participants in the 2009-2014 National Health and Nutrition Examination Survey were analyzed at a cross-sectional level to assess this link. Three biological ages [Klemera-Doubal method (KDM), PhenoAge, and homeostatic dysregulation (HD)] and two measures of accelerated biological aging (BioAgeAccel and PhenoAgeAccel) were set as primary exposure and were calculated. Logistic regression and restricted cubic spline regression were employed to examine the relationship between biological aging and periodontitis. Additionally, Mendelian randomization analysis was conducted to explore the causal connection between accelerated biological aging and periodontitis. After adjusting for age, gender, race, educational level, marital status, ratio of family income, and disease conditions, this study, found a significant association between subjects with older higher biological ages, accelerated biological aging, and periodontitis. Specifically, for a per year increase in the three biological ages (HD, KDM, and PhenoAge), the risk of periodontitis increases by 15%, 3%, and 4% respectively. Individuals who had positive BioAgeAccel or PhenoAgeAccel were 20% or 37% more likely to develop periodontitis compared with those who had negative BioAgeAccel or PhenoAgeAccel. Furthermore, a significant non-linear positive relationship was observed between the three biological ages, accelerated biological aging, and periodontitis. However, the Mendelian randomization analysis indicated no causal effect of accelerated biological aging on periodontitis. Our findings suggest that biological aging may contribute to the risk of periodontitis, highlighting the potential utility of preventive strategies targeting aging-related pathways in reducing periodontitis risk among older adults.

Housekeeping protein-coding genes interrogated with tissue and individual variations.

Housekeeping protein-coding genes are stably expressed genes in cells and tissues that are thought to be engaged in fundamental cellular biological functions. They are often utilized as normalization references in molecular biology research and are especially important in integrated bioinformatic investigations. Prior studies have examined human housekeeping protein-coding genes by analyzing various gene expression datasets. The inclusion of different tissue types significantly impacted the discovery of housekeeping genes. In this report, we investigated particularly individual human subject expression differences in protein-coding genes across different tissue types. We used GTEx V8 gene expression datasets obtained from more than 16,000 human normal tissue samples. Furthermore, the Gini index is utilized to investigate the expression variations of protein-coding genes between tissue and individual donor subjects. Housekeeping protein-coding genes found using Gini index profiles may vary depending on the tissue subtypes investigated, particularly given the diverse sample size collections across the GTEx tissue subtypes. We subsequently selected major tissues and identified subsets of housekeeping genes with stable expression levels among human donors within those tissues. In this work, we provide alternative sets of housekeeping protein-coding genes that show more consistent expression patterns in human subjects across major solid organs. Weblink: https://hpsv.ibms.sinica.edu.tw .

Electrical Double-Layer Transistors Comprising Block Copolymer Electrolytes for Low-Power-Consumption Photodetectors.

Electrical double-layer transistors (EDLTs) have received extensive research attention owing to their exciting advantages of low working voltage, high biocompatibility, and sensitive interfacial properties in ultrasensitive portable sensing applications. Therefore, it is of great interest to reduce photodetectors' operating voltage and power consumption by utilizing photo-EDLT. In this study, a series of block copolymers (BCPs) of poly(4-vinylpyridine)-block-poly(ethylene oxide) (P4VP-b-PEO) with different compositions were applied to formulate polyelectrolyte with indigo carmine salt in EDLT. Accordingly, PEO conduces ion conduction in the BCP electrolyte and enhances the carrier transport capability in the semiconducting channel; P4VP boosts the photocurrent by providing charge-trapping sites during light illumination. In addition, the severe aggregation of PEO is mitigated by forming a BCP structure with P4VP, enhancing the stability and photoresponse of the photo-EDLT. By optimizing the BCP composition, EDLT comprising P4VP16k-b-PEO5k and indigo carmine provides the highest specific detectivity of 2.1 × 107 Jones, along with ultralow power consumptions of 0.59 nW under 450 nm light illumination and 0.32 pW under dark state. The results indicate that photo-EDLT comprising the BCP electrolyte is a practical approach to reducing phototransistors' operating voltage and power consumption.

Overcoming the Blood-Brain Tumor Barrier with Docetaxel-Loaded Mesoporous Silica Nanoparticles for Treatment of Temozolomide-Resistant Glioblastoma.

While temozolomide (TMZ) has been a cornerstone in the treatment of newly diagnosed glioblastoma (GBM), a significant challenge has been the emergence of resistance to TMZ, which compromises its clinical benefits. Additionally, the nonspecificity of TMZ can lead to detrimental side effects. Although TMZ is capable of penetrating the blood-brain barrier (BBB), our research addresses the need for targeted therapy to circumvent resistance mechanisms and reduce off-target effects. This study introduces the use of PEGylated mesoporous silica nanoparticles (MSN) with octyl group modifications (C8-MSN) as a nanocarrier system for the delivery of docetaxel (DTX), providing a novel approach for treating TMZ-resistant GBM. Our findings reveal that C8-MSN is biocompatible in vitro, and DTX@C8-MSN shows no hemolytic activity at therapeutic concentrations, maintaining efficacy against GBM cells. Crucially, in vivo imaging demonstrates preferential accumulation of C8-MSN within the tumor region, suggesting enhanced permeability across the blood-brain tumor barrier (BBTB). When administered to orthotopic glioma mouse models, DTX@C8-MSN notably prolongs survival by over 50%, significantly reduces tumor volume, and decreases side effects compared to free DTX, indicating a targeted and effective approach to treatment. The apoptotic pathways activated by DTX@C8-MSN, evidenced by the increased levels of cleaved caspase-3 and PARP, point to a potent therapeutic mechanism. Collectively, the results advocate DTX@C8-MSN as a promising candidate for targeted therapy in TMZ-resistant GBM, optimizing drug delivery and bioavailability to overcome current therapeutic limitations.

Predictive value of angiopoietin-like protein 8 in metabolic dysfunction-associated fatty liver disease and its progression: A case-control study.

BACKGROUND: The prevalence of metabolic dysfunction-associated fatty liver disease (MAFLD) is rapidly increasing, currently affecting approximately 25% of the global population. Liver fibrosis represents a crucial stage in the development of MAFLD, with advanced liver fibrosis elevating the risks of cirrhosis and hepatocellular carcinoma. Simple serum markers are less effective in diagnosing liver fibrosis compared to more complex markers. However, imaging techniques like transient elastography face limitations in clinical application due to equipment and technical constraints. Consequently, it is imperative to identify a straightforward yet effective method for assessing MAFLD-associated liver fibrosis. AIM: To investigate the predictive value of angiopoietin-like protein 8 (ANGPTL8) in MAFLD and its progression. METHODS: We analyzed 160 patients who underwent abdominal ultrasonography in the Endocrinology Department, Xiaogan Central Hospital affiliated to Wuhan University of Science and Technology, during September 2021-July 2022. Using abdominal ultrasonography and MAFLD diagnostic criteria, among the 160 patients, 80 patients (50%) were diagnosed with MAFLD. The MAFLD group was divided into the liver fibrosis group (n = 23) and non-liver fibrosis group (n = 57) by using a cut-off fibrosis-4 index ≥ 1.45. Logistical regression was used to analyze the risk of MAFLD and the risk factors for its progression. Receiver operating characteristic curves were used to evaluate the predictive value of serum ANGPTL8 in MAFLD and its progression. RESULTS: Compared with non-MAFLD patients, MAFLD patients had higher serum ANGPTL8 and triglyceride-glucose (TyG) index (both P < 0.05). Serum ANGPTL8 (r = 0.576, P < 0.001) and TyG index (r = 0.473, P < 0.001) were positively correlated with MAFLD. Serum ANGPTL8 was a risk factor for MAFLD [odds ratio (OR): 1.123, 95% confidence interval (CI): 1.066-1.184, P < 0.001). Serum ANGPTL8 and ANGPTL8 + TyG index predicted MAFLD [area under the curve (AUC): 0.832 and 0.886, respectively; both P < 0.05]. Compared with MAFLD patients without fibrosis, those with fibrosis had higher serum ANGPTL8 and TyG index (both P < 0.05), and both parameters were positively correlated with MAFLD-associated fibrosis. Elevated serum ANGPTL8 (OR: 1.093, 95%CI: 1.044-1.144, P < 0.001) and TyG index (OR: 2.383, 95%CI: 1.199-4.736, P < 0.013) were risk factors for MAFLD-associated fibrosis. Serum ANGPTL8 and ANGPTL8 + TyG index predicted MAFLD-associated fibrosis (AUC: 0.812 and 0.835, respectively; both P < 0.05). CONCLUSION: The serum levels of ANGPTL8 are elevated and positively correlated with MAFLD. They can serve as predictors for the risk of MAFLD and liver fibrosis, with the ANGPTL8 + TyG index potentially exhibiting even higher predictive value.

Spilled gallstone mimicking intra-abdominal seeding of gallbladder adenocarcinoma: A case report.

BACKGROUND: Gallbladder rupture is common in laparoscopic cholecystectomy because the gallbladder is usually in acute or chronic inflammation status. The gallstones may sometime be spilled into the peritoneal cavity, resulting in intra-abdominal abscess if the gallstones were not retrieved. The diagnosis of intra-abdominal abscess caused by unretrieved gallstone can usually be correctly identified in the routine imaging studies, such as abdominal ultrasonography or computed tomography (CT). Here we present a case of abscess formation from unretrieved gallstone following laparoscopic cholecystectomy, which mimics the imaging findings of metastatic gallbladder adenocarcinoma. CASE SUMMARY: This case described a 78-year-old man who received laparoscopic cholecystectomy and gallbladder adenocarcinoma was diagnosed after surgery. After adjuvant chemotherapy, the following up abdominal CT showed several small nodules at right upper abdomen and peritoneal carcinomatosis is considered. Repeated laparoscopic surgery for the excision of seeding tumor was conducted and the pathological diagnosis of the nodules and mass was inflammatory tissues and gallbladder stone. CONCLUSION: Spilled gallstones are a common complication during laparoscopic cholecystectomy and some gallstones fail to be retrieved due to the size or the restricted view of laparoscopic surgery. For spilled gall bladder stones, surgeons may consider regular computerized tomography follow-up, and if necessary, laparoscopic examination can be used as a means of confirming the diagnostic and treatment.

A Lightweight Image Super-Resolution Reconstruction Algorithm Based on the Residual Feature Distillation Mechanism.

In recent years, the development of image super-resolution (SR) has explored the capabilities of convolutional neural networks (CNNs). The current research tends to use deeper CNNs to improve performance. However, blindly increasing the depth of the network does not effectively enhance its performance. Moreover, as the network depth increases, more issues arise during the training process, requiring additional training techniques. In this paper, we propose a lightweight image super-resolution reconstruction algorithm (SISR-RFDM) based on the residual feature distillation mechanism (RFDM). Building upon residual blocks, we introduce spatial attention (SA) modules to provide more informative cues for recovering high-frequency details such as image edges and textures. Additionally, the output of each residual block is utilized as hierarchical features for global feature fusion (GFF), enhancing inter-layer information flow and feature reuse. Finally, all these features are fed into the reconstruction module to restore high-quality images. Experimental results demonstrate that our proposed algorithm outperforms other comparative algorithms in terms of both subjective visual effects and objective evaluation quality. The peak signal-to-noise ratio (PSNR) is improved by 0.23 dB, and the structural similarity index (SSIM) reaches 0.9607.

Reversible Molecular Conformation Transitions of Smectic Liquid Crystals for Light/Bias-Gated Transistor Memory.

In recent years, organic photonic field-effect transistors have made remarkable progress with the rapid development of conjugated polycrystalline materials. Liquid crystals, with their smooth surface, defined layer thickness, and crystalline structures, are commonly used for these advantages. In this work, a series of smectic liquid crystalline molecules, 2,9-didecyl-dinaphtho-thienothiophene (C10-DNTT), 2,7-didecyl-benzothieno-benzothiopene (C10-BTBT), 3,9-didecyl-dinaphtho-thiophene (C10-DNT), and didecyl-sexithiophene (C10-6T), have been used in photonic transistor memory, functioning as both hole-transport channels and electron traps to investigate systematically the reasons and mechanisms behind the memory behavior of smectic liquid crystals. After thermal annealing, C10-BTBT and C10-6T/C10-DNTT are homeotropically aligned from the smectic A and smectic X phases, respectively. The 3D-ordered structure of these smectic-aligned crystals contributed to efficient photowriting and electrical erasing processes. Among them, the device performance of C10-BTBT was particularly significant, with a memory window of 21 V. The memory ratio could reach 1.5 × 106 and maintain a memory ratio of over 3 orders after 10,000 s, contributing to its smectic A structure. Through the research, we confirmed the memory and light/bias-gated behaviors of these smectic liquid crystalline molecules, attributing them to reversible molecular conformation transitions and the inherent structural inhomogeneity inside the polycrystalline channel layer.