Red blood cell alloimmunization in transfused patients with myelodysplastic syndromes: a retrospective study from northern China.

OBJECTIVE: Alloimmunization against red blood cell (RBC) antigen is an important concern in myelodysplastic syndromes (MDSs) patients with chronic transfusion, causing potential risk for hemolytic reaction and limited supply of compatible blood. However, there is little data addressing RBC alloimmunization in this patient cohort among the Chinese population. This study aims to evaluate the incidence, specificity of antibodies, and RBC units transfused before antibody formation and its significance in a population of patients consistently receiving RhD-matched RBC units. METHODS: We retrospectively reviewed the transfusion and clinical information of all transfused patients with MDS enrolled in our hospital from 2012 to 2022. The cumulative incidence of alloimmunization was analyzed by a Kaplan-Meier plot. Alloimmunization incidence was compared based on different transfused RBC units using the log-rank test. RESULTS: A total of 103 patients with MDS were included in this study; alloantibody formed in 8 (7.8%) patients. Before reaching 32 RBC units, 87.5% of the alloimmunized patients had developed their alloantibodies. All but 1 of the alloantibodies developed were antibodies to Rh antigens. The RBC transfusion intensity and frequency were significantly higher following alloimmunization in the alloimmunized patients (P = .008, P = .008, respectively). CONCLUSION: The antibodies detected mostly involve the Rh system among MDS patients in China. The alloimmunization tended to occur early prior to reaching 32 RBC units in patients with MDS. Rh antigen matching should be considered early in the patient's transfusion history and completed before receiving 32 RBC units.

A Residual Dense Attention Generative Adversarial Network for Microscopic Image Super-Resolution.

With the development of deep learning, the Super-Resolution (SR) reconstruction of microscopic images has improved significantly. However, the scarcity of microscopic images for training, the underutilization of hierarchical features in original Low-Resolution (LR) images, and the high-frequency noise unrelated with the image structure generated during the reconstruction process are still challenges in the Single Image Super-Resolution (SISR) field. Faced with these issues, we first collected sufficient microscopic images through Motic, a company engaged in the design and production of optical and digital microscopes, to establish a dataset. Secondly, we proposed a Residual Dense Attention Generative Adversarial Network (RDAGAN). The network comprises a generator, an image discriminator, and a feature discriminator. The generator includes a Residual Dense Block (RDB) and a Convolutional Block Attention Module (CBAM), focusing on extracting the hierarchical features of the original LR image. Simultaneously, the added feature discriminator enables the network to generate high-frequency features pertinent to the image's structure. Finally, we conducted experimental analysis and compared our model with six classic models. Compared with the best model, our model improved PSNR and SSIM by about 1.5 dB and 0.2, respectively.

Development of Predicting Nomograms for Diffuse Astrocytoma and Anaplastic Astrocytoma: A Study Based on the Surveillance, Epidemiology, and End Results Database.

BACKGROUND: Astrocytoma is a type of adult-type diffuse gliomas that includes diffuse astrocytoma (DA) and anaplastic astrocytoma (AA). However, comprehensive investigations into the risk assessment and prognosis of DA and AA using population-based studies remain noticeably scarce. METHODS: In this study, we developed 2 predictive nomograms to evaluate the susceptibility and prognosis associated with DA and AA. The study cohort comprised 3837 individuals diagnosed with DA or AA between 2010 and 2019 selected from the Surveillance, Epidemiology, and End Results (SEER) database. Independent predictors were identified and used to construct the nomograms for overall death and cancer-specific death rates. The performance of the models was assessed using C-index, calibration curves, and receiver operating characteristic curve, and the clinical applicability was evaluated using decision curve analysis. RESULTS: The receiver operating characteristic curves in this study show excellent clinical applicability and predictive power. Notably, the area under the curves of the training and verification queues was higher than 0.80, thereby cementing the models' precision. Additionally, the calibration plots demonstrate that the anticipated mortality rates strikingly match the measured values. This alignment of figures is sustained in the validation cohort. Furthermore, the decision curve analysis corroborates the models' translational potential, reinforcing their relevance within real-world clinical settings. CONCLUSIONS: The presented nomograms have not only exhibited good predictive performance but also showcased pragmatic clinical utility in prognosticating patient outcomes. Significantly, this will undoubtedly serve as a valuable asset for oncologists, facilitating informed treatment decisions and meticulous follow-up planning.

CHCHD2 up-regulation in Huntington disease mediates a compensatory protective response against oxidative stress.

Huntington disease (HD) is a neurodegenerative disease caused by the abnormal expansion of a polyglutamine tract resulting from a mutation in the HTT gene. Oxidative stress has been identified as a significant contributing factor to the development of HD and other neurodegenerative diseases, and targeting anti-oxidative stress has emerged as a potential therapeutic approach. CHCHD2 is a mitochondria-related protein involved in regulating cell migration, anti-oxidative stress, and anti-apoptosis. Although CHCHD2 is highly expressed in HD cells, its specific role in the pathogenesis of HD remains uncertain. We postulate that the up-regulation of CHCHD2 in HD models represents a compensatory protective response against mitochondrial dysfunction and oxidative stress associated with HD. To investigate this hypothesis, we employed HD mouse striatal cells and human induced pluripotent stem cells (hiPSCs) as models to examine the effects of CHCHD2 overexpression (CHCHD2-OE) or knockdown (CHCHD2-KD) on the HD phenotype. Our findings demonstrate that CHCHD2 is crucial for maintaining cell survival in both HD mouse striatal cells and hiPSCs-derived neurons. Our study demonstrates that CHCHD2 up-regulation in HD serves as a compensatory protective response against oxidative stress, suggesting a potential anti-oxidative strategy for the treatment of HD.

Carrier screening for spinal muscular atrophy in 22913 Chinese reproductive age women.

BACKGROUND: To determine the carrier frequency of, and evaluate a carrier screening program for, spinal muscular atrophy (SMA) in reproductive age women in Shenzhen area. METHODS: A staged screening procedure was used to perform carrier screening for SMA in 22,913 Chinese reproductive age women between 2019 and 2022 in Shenzhen area of China. First, the copy number of exon 7 in the SMN1 gene were detected in women of reproductive age using real-time quantitative polymerase chain reaction. If SMA carriers were detected, their spouses were then recommended to test. Prenatal diagnosis was carried out in couples who were both carriers. RESULTS: A total of 389 women were found to be SMA carriers (1.70%, 95% CI: 1.53%-1.87%), indicating the carrier prevalence was approximately 1:59. Despite the proportion of nonpregnant women increased from 37.96% in 2019 to 58.18% in 2022 (p < 0.05) among the 22,913 reproductive age women, the recall rate of spouses was still not high (62.21%, 95% CI: 57.39%-67.03%). Eight partners were found to be SMA carriers and two fetuses were determined to have SMA with no copies of the SMN1 gene. CONCLUSION: Although the acceptability and awareness of SMA carrier screening in Chinese population has increased in recent years, it still fails to reach the ideal expectation. Our experience may provide a basis for and facilitate the popularization of SMA carrier screening in Shenzhen area.

Competing Risk Model to Determine the Prognostic Factors for Patients with Gliosarcoma.

BACKGROUND: Gliosarcoma (GSM) is a highly aggressive variant of brain cancer with an extremely unfavorable prognosis. Prognosis is not feasible by traditional methods because of a lack of staging criteria, and the present study aims to screen more detailed demographic factors to predict the prognostic factors of the tumors. METHODS: For this study, we extracted data of patients diagnosed with GSM from the SEER (Surveillance Epidemiology and End Results) database between 2000 and 2019. To account for the influence of competing risks, we used a Cumulative Incidence Function. Subsequently, univariate analysis was conducted to evaluate the individual variables under investigation. Specifically for patients with GSM, we generated cumulative risk curves for specific mortality outcomes and events related to competing risks. In addition, we used both univariate and multivariate Cox analysis to account for non-GSM-related deaths that may confound our research. RESULTS: The competing risk model showed that age, marital status, tumor size, and adjuvant therapy were prognostic factors in GSM-related death. The analysis results showed that older age (60-70 years, ≥71 years) and larger tumor size (≥5.3 cm) significantly increased the risk of GSM-related death. Conversely, surgical intervention, chemotherapy, and being single were identified as protective factors against GSM-related death. CONCLUSIONS: Our study using a competing risk model provided valuable insights into the prognostic factors associated with GSM-related death. Further research and clinical interventions targeted at minimizing these risk factors and promoting the use of protective measures may contribute to improved outcomes and reduced mortality for patients with GSM.

The emerging roles of N6-methyladenosine RNA modifications in thyroid cancer.

Thyroid cancer (TC) is the most predominant malignancy of the endocrine system, with steadily growing occurrence and morbidity worldwide. Although diagnostic and therapeutic methods have been rapidly developed in recent years, the underlying molecular mechanisms in the pathogenesis of TC remain enigmatic. The N6-methyladenosine(m6A) RNA modification is designed to impact RNA metabolism and further gene regulation. This process is intricately regulated by a variety of regulators, such as methylases and demethylases. Aberrant m6A regulators expression is related to the occurrence and development of TC and play an important role in drug resistance. This review comprehensively analyzes the effect of m6A methylation on TC progression and the potential clinical value of m6A regulators as prognostic markers and therapeutic targets in this disease.

Systematical Investigation of Flicker Noise in 14 nm FinFET Devices towards Stochastic Computing Application.

Stochastic computing (SC) is widely known for its high error tolerance and efficient computing ability of complex functions with remarkably simple logic gates. The noise of electronic devices is widely used to be the entropy source due to its randomness. Compared with thermal noise and random telegraph noise (RTN), flicker noise is favored by researchers because of its high noise density. Meanwhile, unlike using RRAM, PCRAM and other emerging memory devices as the entropy source, using logic devices does not require any additional process steps, which is significant for industrialization. In this work, we systematically and statistically studied the 1/f noise characteristics of 14 nm FinFET, and found that miniaturizing the channel area of the device or lowering the ambient temperature can effectively increase the 1/f noise density of the device. This is of great importance to improve the accuracy of the SC system and simplify the complexity of the stochastic number generator (SNG) circuit. At the same time, these rules of 1/f noise characteristics in FinFET devices can provide good guidance for our device selection in circuit design.

A low-power vertical dual-gate neurotransistor with short-term memory for high energy-efficient neuromorphic computing.

Neuromorphic computing aims to emulate the computing processes of the brain by replicating the functions of biological neural networks using electronic counterparts. One promising approach is dendritic computing, which takes inspiration from the multi-dendritic branch structure of neurons to enhance the processing capability of artificial neural networks. While there has been a recent surge of interest in implementing dendritic computing using emerging devices, achieving artificial dendrites with throughputs and energy efficiency comparable to those of the human brain has proven challenging. In this study, we report on the development of a compact and low-power neurotransistor based on a vertical dual-gate electrolyte-gated transistor (EGT) with short-term memory characteristics, a 30 nm channel length, a record-low read power of ~3.16 fW and a biology-comparable read energy of ~30 fJ. Leveraging this neurotransistor, we demonstrate dendrite integration as well as digital and analog dendritic computing for coincidence detection. We also showcase the potential of neurotransistors in realizing advanced brain-like functions by developing a hardware neural network and demonstrating bio-inspired sound localization. Our results suggest that the neurotransistor-based approach may pave the way for next-generation neuromorphic computing with energy efficiency on par with those of the brain.

Autophagy in sepsis-induced acute lung injury: Friend or foe?

Sepsis-induced acute lung injury (ALI) is a life-threatening syndrome with high mortality and morbidity, resulting in a heavy burden on family and society. As a key factor that maintains cellular homeostasis, autophagy is regarded as a self-digesting process by which damaged organelles and useless proteins are recycled for cell metabolism, and it thus plays a crucial role during physiological and pathological processes. Recent studies have indicated that autophagy is involved in the pathophysiological process of sepsis-induced ALI, including cell apoptosis, inflammation, and mitochondrial dysfunction, which indicates that regulating autophagy may be beneficial for this disease. However, the role of autophagy in the etiology and treatment of sepsis-induced ALI is not well characterized. This review summarizes the autophagy-related signaling pathways in sepsis-induced ALI, as well as focuses on the dual role of autophagy and its regulation by non-coding RNAs during disease progression, for the development of potential therapeutic strategies in this disease.

A tumor mutational burden-derived immune computational framework selects sensitive immunotherapy/chemotherapy for lung adenocarcinoma populations with different prognoses.

Background: Lung adenocarcinoma (LUAD) kills millions of people every year. Recently, FDA and researchers proved the significance of high tumor mutational burden (TMB) in treating solid tumors. But no scholar has constructed a TMB-derived computing framework to select sensitive immunotherapy/chemotherapy for the LUAD population with different prognoses. Methods: The datasets were collected from TCGA, GTEx, and GEO. We constructed the TMB-derived immune lncRNA prognostic index (TILPI) computing framework based on TMB-related genes identified by weighted gene co-expression network analysis (WGCNA), oncogenes, and immune-related genes. Furthermore, we mapped the immune landscape based on eight algorithms. We explored the immunotherapy sensitivity of different prognostic populations based on immunotherapy response, tumor immune dysfunction and exclusion (TIDE), and tumor inflammation signature (TIS) model. Furthermore, the molecular docking models were constructed for sensitive drugs identified by the pRRophetic package, oncopredict package, and connectivity map (CMap). Results: The TILPI computing framework was based on the expression of TMB-derived immune lncRNA signature (TILncSig), which consisted of AC091057.1, AC112721.1, AC114763.1, AC129492.1, LINC00592, and TARID. TILPI divided all LUAD patients into two populations with different prognoses. The random grouping verification, survival analysis, 3D PCA, and ROC curve (AUC=0.74) firmly proved the reliability of TILPI. TILPI was associated with clinical characteristics, including smoking and pathological stage. Furthermore, we estimated three types of immune cells threatening the survival of patients based on multiple algorithms. They were macrophage M0, T cell CD4 Th2, and T cell CD4 memory activated. Nevertheless, five immune cells, including B cell, endothelial cell, eosinophil, mast cell, and T cell CD4 memory resting, prolonged the survival. In addition, the immunotherapy response and TIDE model proved the sensitivity of the low-TILPI population to immunotherapy. We also identified seven intersected drugs for the LUAD population with poor prognosis, which included docetaxel, gemcitabine, paclitaxel, palbociclib, pyrimethamine, thapsigargin, and vinorelbine. Their molecular docking models and best binding energy were also constructed and calculated. Conclusions: We divided all LUAD patients into two populations with different prognoses. The good prognosis population was sensitive to immunotherapy, while the people with poor prognosis benefitted from 7 drugs.

Evaluation of high oleic sunflower oil oleogels with beeswax, beeswax-glyceryl monopalmitate, and beeswax-Span80 in cookie preparation.

BACKGROUND: Shortening is used widely in cookie preparation to improve quality and texture. However, large amounts of saturated and trans fatty acids present in shortening have adverse effects on human health, and much effort has been made to reduce the use of shortening. The use of oleogels might be a suitable alternative. In this study, the oleogels of high oleic sunflower oil with beeswax (BW), BW-glyceryl monopalmitate (BW-GMP), and BW-Span80 (BW-S80) were prepared and their suitability to replace shortening in cookie preparation was evaluated. RESULTS: The solid fat content of BW, BW-GMP, and BW-S80 oleogels was significantly lower than that of commercial shortening when the temperature was not higher than 35 °C. However, the oil-binding capacity of these oleogels was almost similar to that of shortening. The crystals in the shortening and oleogels were ß' form mainly; however, the morphology of crystal aggregates in these oleogels was different from that of shortening. The textural and rheological properties of doughs prepared with the oleogels were similar, and clearly different from those of dough with commercial shortening. The breaking strengths of cookies made with oleogels were lower than that of cookies prepared with shortening. However, cookies containing BW-GMP and BW-S80 oleogels were similar in density and color to those prepared with shortening. CONCLUSION: The textural properties and color of cookies with BW-GMP and BW-S80 oleogels were very similar to those of the cookies containing commercial shortening. The BW-GMP and BW-S80 oleogels could act as alternatives to shortening in the preparation of cookies. © 2023 Society of Chemical Industry.

M1ARegpred: Epitranscriptome Target Prediction of N1-methyladenosine (m1A) Regulators Based on Sequencing Features and Genomic Features.

BACKGROUND: N1-methyladenosine (m1A) is a reversible post-transcriptional modification in mRNA, which has been proved to play critical roles in various biological processes through interaction with different m1A regulators. There are several m1A regulators existing in the human genome, including YTHDF1-3 and YTHDC1. METHODS: Several techniques have been developed to identify the substrates of m1A regulators, but their binding specificity and biological functions are not yet fully understood due to the limitations of wet-lab approaches. Here, we submitted the framework m1ARegpred (m1A regulators substrate prediction), which is based on machine learning and the combination of sequence-derived and genome-derived features. RESULTS: Our framework achieved area under the receiver operating characteristic (AUROC) scores of 0.92 in the full transcript model and 0.857 in the mature mRNA model, showing an improvement compared to the existing sequence-derived methods. In addition, motif search and gene ontology enrichment analysis were performed to explore the biological functions of each m1A regulator. CONCLUSIONS: Our work may facilitate the discovery of m1A regulators substrates of interest, and thereby provide new opportunities to understand their roles in human bodies.

A 13 µW Analog Front-End with RRAM-Based Lowpass FIR Filter for EEG Signal Detection.

This brief presents an analog front-end (AFE) for the detection of electroencephalogram (EEG) signals. The AFE is composed of four sections, chopper-stabilized amplifiers, ripple suppression circuit, RRAM-based lowpass FIR filter, and 8-bit SAR ADC. This is the first time that an RRAM-based lowpass FIR filter has been introduced in an EEG AFE, where the bio-plausible characteristics of RRAM are utilized to analyze signals in the analog domain with high efficiency. The preamp uses the symmetrical OTA structure, reducing power consumption while meeting gain requirements. The ripple suppression circuit greatly improves noise characteristics and offset voltage. The RRAM-based low-pass filter achieves a 40 Hz cutoff frequency, which is suitable for the analysis of EEG signals. The SAR ADC adopts a segmented capacitor structure, effectively reducing the capacitor switching power consumption. The chip prototype is designed in 40 nm CMOS technology. The overall power consumption is approximately 13 µW, achieving ultra-low-power operation.

Ultrasensitive detection of four organic arsenic compounds at the same time using a five-link cardboard-based assay.

In order to effectively control the excessive use of organic arsenic reagents in livestock and poultry products, there is an urgent need to develop a method for rapid detection of multiple organic arsenic reagents. In this study, two haptens were designed and derivatized around the structural formula of roxarsone, and a highly-sensitive group-selective mAb 3F2 was prepared, which can simultaneously detect roxarsone, 4-aminophenylarsonic acid, 2-aminophenylarsonic acid and phenylarsonic acid. We further developed a colloidal gold immunochromatographic test strip (ICS) and prepared a five-link card that can simultaneously detect four organic arsenics in chicken and pork samples. Its quantitative detection limits (LOQ) for the four compounds in chicken and pork samples were 0.06 and 0.32 ng/mL, 0.11 and 0.29 ng/mL, 0.34 and 0.99 ng/mL, and 0.88 and 1.5 ng/mL, respectively. This multi-ICS detection provides a powerful tool for the on-site detection and rapid screening of organic arsenic reagents in actual samples.

Reflow Soldering Capability Improvement by Utilizing TaN Interfacial Layer in 1Mbit RRAM Chip.

We investigated the thermal stability of a 1Mbit OxRRAM array embedded in 28 nm COMS technology. A back-end-of-line (BEOL) solution with a TaN-Ta interfacial layer was proposed to eliminate the failure rate after reflow soldering assembly at 260 °C. By utilizing a TaN-Ta interfacial layer (IL), the oxygen defects in conductive filament were redistributed, and electromigration lifetimes of Cu-based damascene interconnects were improved, which contributed to optimization. This work provides a potential solution for the practical application of embedded RRAM beyond the 28 nm technology node.

Long-Term Accuracy Enhancement of Binary Neural Networks Based on Optimized Three-Dimensional Memristor Array.

In embedded neuromorphic Internet of Things (IoT) systems, it is critical to improve the efficiency of neural network (NN) edge devices in inferring a pretrained NN. Meanwhile, in the paradigm of edge computing, device integration, data retention characteristics and power consumption are particularly important. In this paper, the self-selected device (SSD), which is the base cell for building the densest three-dimensional (3D) architecture, is used to store non-volatile weights in binary neural networks (BNN) for embedded NN applications. Considering that the prevailing issues in written data retention on the device can affect the energy efficiency of the system's operation, the data loss mechanism of the self-selected cell is elucidated. On this basis, we introduce an optimized method to retain oxygen ions and prevent their diffusion toward the switching layer by introducing a titanium interfacial layer. By using this optimization, the recombination probability of Vo and oxygen ions is reduced, effectively improving the retention characteristics of the device. The optimization effect is verified using a simulation after mapping the BNN weights to the 3D VRRAM array constructed by the SSD before and after optimization. The simulation results showed that the long-term recognition accuracy (greater than 105 s) of the pre-trained BNN was improved by 24% and that the energy consumption of the system during training can be reduced 25,000-fold while ensuring the same accuracy. This work provides high storage density and a non-volatile solution to meet the low power consumption and miniaturization requirements of embedded neuromorphic applications.

An ultrasensitive colloidal gold immunosensor to simultaneously detect 12 beta (2)-adrenergic agonists.

In this study, we first prepared a selective monoclonal antibody against 12 beta (2)-adrenergic agonists (Salbutamol, Clenbuterol, Brombuterol, Clenpenterol, Mabuterol, Carbuterol, Cimbuterol, Mapenterol, Pirbuterol, Terbutaline, Cimaterol, and Clenproperol). Then three haptens were designed and derived, among which, haptenS3 used the amino group of the salbutamol analog to derive a carboxyl group containing a spacer, which is unique to this study. The half-maximal inhibitory concentration (IC50) values were 0.35 ng/mL (Salbutamol), 0.42 ng/mL (Clenbuterol), 0.78 ng/mL (Brombuterol), 0.88 ng/mL (Clenpenterol), 1.34 ng/mL (Mabuterol), 1.38 ng/mL (Carbuterol), 1.71 ng/mL (Cimbuterol), 2.24 ng/mL (Mapenterol), 2.25 ng/mL (Pirbuterol), 2.27 ng/mL (Terbutaline), 3.49 ng/mL (Cimaterol), and 4.89 ng/mL (Clenproperol). We further developed a monoclonal antibody-based colloidal gold immunochromatographic test strip for screening and detecting 12 beta (2)-adrenergic agonists in swine urine and lamb samples. The immunochromatographic method developed in this study is a suitable tool for the on-site rapid detection and screening of beta (2)-adrenergic agonists in swine urine and lamb samples.

Pharmacokinetics of yunaconitine and indaconitine in mouse blood by UPLC-MS/MS.

Yunaconitine and indaconitine are active ingredients from the rhizomes of Aconitum plants. In this study, an ultra-high-performance liquid chromatography tandem mass spectrometry (UPLC-MS/MS) method was developed to measure the concentrations of the yunaconitine and indaconitine in mouse blood, and the method was applied in measuring the pharmacokinetics of the two alkaloids after oral and intravenous administration. A UPLC HSS T3 column (2.1 mm × 100 mm, 1.8 µm particle size) was used for chromatographic separation by gradient elution using acetonitrile-water (0.1% formic acid) as the mobile phase at a flow rate of 0.4 mL/min. Multiple reaction monitoring (MRM) mode and electrospray ionization (ESI) (positive-ion mode) were used to monitor the transitions of each analyte by tandem mass spectrometry for quantitative analysis. Yunaconitine and indaconitine were administered to the mice orally at 2 mg/kg and intravenously at 0.05 mg/kg. Blood was collected at various time intervals, and the blood samples were processed after collection and analyzed by UPLC-MS/MS. The standard curve generated for each analyte was linear over the concentration range of 0.5-500 ng/mL. The intra-day and inter-day accuracy of yunaconitine and indaconitine were 90%-103% and 86%-106%, respectively, and the precision (RSD, %) was less than 15% for both intra-day and inter-day measurements. The matrix effect ranged from 96% to 109%, and the recovery was higher than 72%. The UPLC-MS/MS method developed herein was successfully applied to measuring the pharmacokinetic parameters of yunaconitine and indaconitine in mice after intravenous and oral administration. The bioavailability of yunaconitine and indaconitine were 27.4% and 25.8%, respectively.