Regulation of FSP1 myristoylation by NADPH: A novel mechanism for ferroptosis inhibition.

Excitotoxicity is a prevalent pathological event in neurodegenerative diseases. The involvement of ferroptosis in the pathogenesis of excitotoxicity remains elusive. Transcriptome analysis has revealed that cytoplasmic reduced nicotinamide adenine dinucleotide phosphate (NADPH) levels are associated with susceptibility to ferroptosis-inducing compounds. Here we show that exogenous NADPH, besides being reductant, interacts with N-myristoyltransferase 2 (NMT2) and upregulates the N-myristoylated ferroptosis suppressor protein 1 (FSP1). NADPH increases membrane-localized FSP1 and strengthens resistance to ferroptosis. Arg-291 of NMT2 is critical for the NADPH-NMT2-FSP1 axis-mediated suppression of ferroptosis. This study suggests that NMT2 plays a pivotal role by bridging NADPH levels and neuronal susceptibility to ferroptosis. We propose a mechanism by which the NADPH regulates N-myristoylation, which has important implications for ferroptosis and disease treatment.

Loss of CREBBP and KMT2D cooperate to accelerate lymphomagenesis and shape the lymphoma immune microenvironment.

Despite regulating overlapping gene enhancers and pathways, CREBBP and KMT2D mutations recurrently co-occur in germinal center (GC) B cell-derived lymphomas, suggesting potential oncogenic cooperation. Herein, we report that combined haploinsufficiency of Crebbp and Kmt2d induces a more severe mouse lymphoma phenotype (vs either allele alone) and unexpectedly confers an immune evasive microenvironment manifesting as CD8+ T-cell exhaustion and reduced infiltration. This is linked to profound repression of immune synapse genes that mediate crosstalk with T-cells, resulting in aberrant GC B cell fate decisions. From the epigenetic perspective, we observe interaction and mutually dependent binding and function of CREBBP and KMT2D on chromatin. Their combined deficiency preferentially impairs activation of immune synapse-responsive super-enhancers, pointing to a particular dependency for both co-activators at these specialized regulatory elements. Together, our data provide an example where chromatin modifier mutations cooperatively shape and induce an immune-evasive microenvironment to facilitate lymphomagenesis.

Efficient Neural Networks on the Edge with FPGAs by Optimizing an Adaptive Activation Function.

The implementation of neural networks (NNs) on edge devices enables local processing of wireless data, but faces challenges such as high computational complexity and memory requirements when deep neural networks (DNNs) are used. Shallow neural networks customized for specific problems are more efficient, requiring fewer resources and resulting in a lower latency solution. An additional benefit of the smaller network size is that it is suitable for real-time processing on edge devices. The main concern with shallow neural networks is their accuracy performance compared to DNNs. In this paper, we demonstrate that a customized adaptive activation function (AAF) can meet the accuracy of a DNN. We designed an efficient FPGA implementation for a customized segmented spline curve neural network (SSCNN) structure to replace the traditional fixed activation function with an AAF. We compared our SSCNN with different neural network structures such as a real-valued time-delay neural network (RVTDNN), an augmented real-valued time-delay neural network (ARVTDNN), and deep neural networks with different parameters. Our proposed SSCNN implementation uses 40% fewer hardware resources and no block RAMs compared to the DNN with similar accuracy. We experimentally validated this computationally efficient and memory-saving FPGA implementation of the SSCNN for digital predistortion of radio-frequency (RF) power amplifiers using the AMD/Xilinx RFSoC ZCU111. The implemented solution uses less than 3% of the available resources. The solution also enables an increase of the clock frequency to 221.12 MHz, allowing the transmission of wide bandwidth signals.

Investigating microglia-neuron crosstalk by characterizing microglial contamination in human and mouse patch-seq datasets.

Microglia are cells with diverse roles, including the regulation of neuronal excitability. We leveraged Patch-seq to assess the presence and effects of microglia in the local microenvironment of recorded neurons. We first quantified the amounts of microglial transcripts in three Patch-seq datasets of human and mouse neocortical neurons, observing extensive contamination. Variation in microglial contamination was explained foremost by donor identity, particularly in human samples, and additionally by neuronal cell type identity in mice. Gene set enrichment analysis suggests that microglial contamination is reflective of activated microglia, and that these transcriptional signatures are distinct from those captured via single-nucleus RNA-seq. Finally, neurons with greater microglial contamination differed markedly in their electrophysiological characteristics, including lowered input resistances and more depolarized action potential thresholds. Our results generalize beyond Patch-seq to suggest that activated microglia may be widely present across brain slice preparations and contribute to neuron- and donor-related electrophysiological variability in vitro.

CRISPR-Cas and catalytic hairpin assembly technology for target-initiated amplification detection of pancreatic cancer specific tsRNAs.

Transfer RNA-derived small RNAs (tsRNAs) tRF-LeuCAG-002 (ts3011a RNA) is a novel class of non-coding RNAs biomarker for pancreatic cancer (PC). Reverse transcription polymerase chain reaction (RT-qPCR) has been unfit for community hospitals that are short of specialized equipment or laboratory setups. It has not been reported whether isothermal technology can be used for detection, because the tsRNAs have rich modifications and secondary structures compared with other non-coding RNAs. Herein, we have employed a catalytic hairpin assembly (CHA) circuit and clustered regularly interspaced short palindromic repeats (CRISPR) to develop an isothermal and target-initiated amplification method for detecting ts3011a RNA. In the proposed assay, the presence of target tsRNA triggers the CHA circuit that transforms new DNA duplexes to activate collateral cleavage activity of CRISPR-associated proteins (CRISPR-Cas) 12a, achieving cascade signal amplification. This method showed a low detection limit of 88 aM at 37 °C within 2 h. Moreover, it was demonstrated for the first time that, this method is less likely to produce aerosol contamination than RT-qPCR by simulating aerosol leakage experiments. This method has good consistency with RT-qPCR in the detection of serum samples and showed great potential for PC-specific tsRNAs point-of-care testing (POCT).

aMAP Score and Its Combination With Liver Stiffness Measurement Accurately Assess Liver Fibrosis in Chronic Hepatitis B Patients.

BACKGROUND & AIMS: The changes in liver stiffness measurement (LSM) are unreliable to estimate regression of fibrosis during antiviral treatment for chronic hepatitis B (CHB) patients. The age-male-albumin-bilirubin-platelets score (aMAP), as an accurate hepatocellular carcinoma risk score, may reflect the liver fibrosis stage. Here, we aimed to evaluate the performance of aMAP for diagnosing liver fibrosis in CHB patients with or without treatment. METHODS: A total of 2053 patients from 2 real-world cohorts and 2 multicentric randomized controlled trials in China were enrolled, among which 2053 CHB patients were included in the cross-sectional analysis, and 889 CHB patients with paired liver biopsies before and after 72 or 104 weeks of treatment were included in the longitudinal analysis. RESULTS: In the cross-sectional analysis, the areas under the receiver operating characteristic curve of aMAP in diagnosing cirrhosis and advanced fibrosis were 0.788 and 0.757, which were comparable with or significantly higher than those of the fibrosis index based on 4 factors and the aspartate aminotransferase-platelet ratio. The stepwise approach using aMAP and LSM further improved performance in detecting cirrhosis and advanced fibrosis with the smallest uncertainty area (29.7% and 46.2%, respectively) and high accuracy (82.3% and 79.8%, respectively). In the longitudinal analysis, we established a novel model (aMAP-LSM model) by calculating aMAP and LSM results before and after treatment, which had satisfactory performance in diagnosing cirrhosis and advanced fibrosis after treatment (area under the receiver operating characteristic curve, 0.839 and 0.840, respectively), especially for those with a significant decrease in LSM after treatment (vs LSM alone, 0.828 vs 0.748; P < .001 [cirrhosis]; 0.825 vs 0.750; P < .001 [advanced fibrosis]). CONCLUSIONS: The aMAP score is a promising noninvasive tool for diagnosing fibrosis in CHB patients. The aMAP-LSM model could accurately estimate fibrosis stage for treated CHB patients.

Real-life impact of tenofovir disoproxil fumarate and entecavir therapy on lipid profile, glucose, and uric acid in chronic hepatitis B patients.

The impact of long-term nucleos(t)ide analogs treatment on host metabolism is a concern. Hence, we conducted this study to compare the effect of entecavir (ETV) and tenofovir disoproxil fumarate (TDF) on metabolic parameters among chronic hepatitis B (CHB) patients. In this real-life retrospective study, 2030 CHB outpatients treated with ETV or TDF at Nanfang Hospital, China, were included. For treatment-naïve patients, pretreatment and semiannual metabolic parameters were collected. For treatment-experienced patients, metabolic parameters were collected at the first visit. Propensity score matching (PSM) was used to balance the effects of potential confounding factors. Among 122 treatment-naïve patients and 1908 treatment-experienced patients, ETV-treated patients were older with a higher percentage of metabolic syndrome. After PSM, the characteristics were comparable between the two groups. For treatment-naïve patients, four lipid parameters, including total cholesterol (TC), low-density lipoprotein (LDL), high-density lipoprotein, and triglyceride levels showed a decreasing trend during the 42-month TDF treatment, while they remained relatively stable or increased during ETV treatment. At Month 30, the levels of TC and LDL among TDF-treated patients were significantly lower than those among ETV-treated patients (TC: 4.7 mmol/L vs. 3.9 mmol/L, p = 0.004; LDL: 3.0 mmol/L vs. 2.4 mmol/L, p = 0.009). For treatment-experienced patients, we also observed lower levels of lipid parameters in patients with different durations of TDF treatment. The levels of glucose and uric acid were similar among ETV- and TDF-treated patients. TDF has a lipid-lowering effect in CHB patients, which provides a basis for the selection of antiviral drugs for aging CHB patients.

Sexual Dysfunction in Patients with Chronic Hepatitis B: Prevalence and Risk Factors.

BACKGROUND: Sexual dysfunction (SD) is an increasingly serious global problem that has adverse effects on the physical and mental health of patients. AIM: This study aimed to investigate the prevalence of SD and its related factors in patients with chronic hepatitis B (CHB). METHODS: A total of 673 outpatients with CHB from October 2019 to December 2020 were included in the analysis. Demographic and clinical information was collected at enrolment. The Arizona Sexual Experiences Scale was used to evaluate SD. OUTCOMES: The primary outcome measure was the prevalence of SD in CHB patients and its associated factors. Secondary outcomes were the corresponding scores in five domains of ASEX: drive, arousal, lubrication and/or erection, orgasm and satisfaction from orgasm. RESULTS: The average age of patients was 47.0 years, with 85.6% male and 88.1% with cirrhosis. The SD prevalence was 25.4% and was increased with the decrease in liver function reserve (Child-Pugh A vs Child-Pugh B: 24.6% vs 44.8%, P = .016), the progression of liver fibrosis (FIB-4 < 1.45, 1.45-3.25, and > 3.25: 21.3%, 26.5%, and 34.4%, respectively; P < .001), and the aggravation of depression (without, mild, and moderate to severe: 18.1%, 33.6%, and 34.2%, respectively; P < .001). In multivariate analysis, SD was independently correlated with female sex (OR: 5.627, 95% CI: 3.501 - 9.044, P < .001), liver fibrosis (OR: 1.730, 95% CI: 1.054 - 2.842, P = .030), depression (OR: 2.290, 95% CI: 1.564 - 3.354, P < .001), and frequent diarrhea and/or upper respiratory tract infection/urinary system infection (OR: 2.162, 95% CI: 1.313-3.560, P = .002). CLINICAL IMPLICATIONS: This study revealed the current situation of SD in CHB patients in China, and appealed to clinicians to pay attention to the physical and mental health of the CHB patients. STRENGTHS AND LIMITATIONS: This study has a large sample size and detailed demographic and clinical data. It evaluated the relationship between SD and liver function reserve and liver fibrosis degree, and compared gender differences of SD. However, this study is a cross-sectional study design and does not include healthy controls. The effects of conflicts between the couple, SD in a partner, antidepressants and hormone changes on SD were not analyzed. CONCLUSION: SD in CHB patients was highly prevalent, and its prevalence increased significantly with the deterioration of liver function reserve, liver fibrosis and depression. Additional longitudinal studies are needed to further explore its causality. Xingmei L, Siru Z, Junhua Y, et al. Sexual Dysfunction in Patients with Chronic Hepatitis B: Prevalence and Risk Factors. J Sex Med 2022;19:207-215.

TIGAR plays neuroprotective roles in KA-induced excitotoxicity through reducing neuroinflammation and improving mitochondrial function.

Excitotoxicity refers to the ability of excessive extracellular excitatory amino acids to damage neurons via receptor activation. It is a crucial pathogenetic process in neurodegenerative diseases. TP53 is confirmed to be involved in excitotoxicity. It is demonstrated that TP53 induced glycolysis and apoptotic regulator (TIGAR)-regulated metabolic pathway can protect against neuronal injury. However, the role of TIGAR in excitotoxicity and specific mechanisms is still unknown. In this study, an in vivo excitotoxicity model was constructed via stereotypical kainic acid (KA) injection into the striatum of mice. KA reduced TIGAR expression levels, neuroinflammatory responses and mitochondrial dysfunction. TIGAR overexpression could reverse KA-induced neuronal injury by reducing neuroinflammation and improving mitochondrial function, thereby exerting neuroprotective effects. Therefore, this study could provide a potential therapeutic target for neurodegenerative diseases.

[Effect of ozone oil for prevention and treatment of sorafenib-induced hand-foot skin reactions: a randomized controlled trial].

OBJECTIVE: To compare the effects of medical ozone oil and urea ointment for prevention and treatment of hand-foot skin reaction (HFSR) caused by sorafenib in patients with hepatocellular carcinoma (HCC). METHODS: A total of 99 patients diagnosed with advanced HCC according to National Comprehensive Cancer Network (NCCN) who were scheduled to receive sorafenib treatment for the first time were enrolled in this study between April, 2018 and January, 2020. The patients were randomized into medical ozone oil group (n=49) and urea ointment group (control group, n=49) for treatment with local application of 1 mL medical ozone oil (experimental group) and 10% urea ointment (2 g) on the palm and plantar skin (including the fingers and joints) for 12 weeks (3 times per day) starting at the beginning of sorafenib treatment, respectively. The patients were observed for occurrence of HFSR every 2 weeks for 14 weeks. RESULTS: Eight patients were excluded for poor compliance or protocol violations, leaving a total of 91 patients for analysis, including 44 in medical ozone oil group and 47 in urea ointment group. Sixteen (36.4%) of patients in ozone oil group developed HFSR, a rate significantly lower than that in urea ointment group (57.4%; P < 0.05). The incidence of grade 2/3 HFSR was also lower in ozone oil group than in urea ointment group (15.9% [7/44] vs 27.7 [13/47]). CONCLUSIONS: Medical ozone oil can significantly reduce the incidence and severity of HFSR to improve the quality of life of HCC patients receiving sorafenib treatment.

Intelligent whole-blood imaging flow cytometry for simple, rapid, and cost-effective drug-susceptibility testing of leukemia.

Drug susceptibility (also called chemosensitivity) is an important criterion for developing a therapeutic strategy for various cancer types such as breast cancer and leukemia. Recently, functional assays such as high-content screening together with genomic analysis have been shown to be effective for predicting drug susceptibility, but their clinical applicability is poor since they are time-consuming (several days long), labor-intensive, and costly. Here we present a highly simple, rapid, and cost-effective liquid biopsy for ex vivo drug-susceptibility testing of leukemia. The method is based on an extreme-throughput (>1 million cells per second), label-free, whole-blood imaging flow cytometer with a deep convolutional autoencoder, enabling image-based identification of the drug susceptibility of every single white blood cell in whole blood within 24 hours by simply flowing a drug-treated whole blood sample as little as 500 µL into the imaging flow cytometer without labeling. Our results show that the method accurately evaluates the drug susceptibility of white blood cells from untreated patients with acute lymphoblastic leukemia. Our method holds promise for affordable precision medicine.

Optofluidic time-stretch quantitative phase microscopy.

Innovations in optical microscopy have opened new windows onto scientific research, industrial quality control, and medical practice over the last few decades. One of such innovations is optofluidic time-stretch quantitative phase microscopy - an emerging method for high-throughput quantitative phase imaging that builds on the interference between temporally stretched signal and reference pulses by using dispersive properties of light in both spatial and temporal domains in an interferometric configuration on a microfluidic platform. It achieves the continuous acquisition of both intensity and phase images with a high throughput of more than 10,000 particles or cells per second by overcoming speed limitations that exist in conventional quantitative phase imaging methods. Applications enabled by such capabilities are versatile and include characterization of cancer cells and microalgal cultures. In this paper, we review the principles and applications of optofluidic time-stretch quantitative phase microscopy and discuss its future perspective.

Label-free detection of cellular drug responses by high-throughput bright-field imaging and machine learning.

In the last decade, high-content screening based on multivariate single-cell imaging has been proven effective in drug discovery to evaluate drug-induced phenotypic variations. Unfortunately, this method inherently requires fluorescent labeling which has several drawbacks. Here we present a label-free method for evaluating cellular drug responses only by high-throughput bright-field imaging with the aid of machine learning algorithms. Specifically, we performed high-throughput bright-field imaging of numerous drug-treated and -untreated cells (N = ~240,000) by optofluidic time-stretch microscopy with high throughput up to 10,000 cells/s and applied machine learning to the cell images to identify their morphological variations which are too subtle for human eyes to detect. Consequently, we achieved a high accuracy of 92% in distinguishing drug-treated and -untreated cells without the need for labeling. Furthermore, we also demonstrated that dose-dependent, drug-induced morphological change from different experiments can be inferred from the classification accuracy of a single classification model. Our work lays the groundwork for label-free drug screening in pharmaceutical science and industry.

Label-free detection of aggregated platelets in blood by machine-learning-aided optofluidic time-stretch microscopy.

According to WHO, about 10 million new cases of thrombotic disorders are diagnosed worldwide every year. Thrombotic disorders, including atherothrombosis (the leading cause of death in the US and Europe), are induced by occlusion of blood vessels, due to the formation of blood clots in which aggregated platelets play an important role. The presence of aggregated platelets in blood may be related to atherothrombosis (especially acute myocardial infarction) and is, hence, useful as a potential biomarker for the disease. However, conventional high-throughput blood analysers fail to accurately identify aggregated platelets in blood. Here we present an in vitro on-chip assay for label-free, single-cell image-based detection of aggregated platelets in human blood. This assay builds on a combination of optofluidic time-stretch microscopy on a microfluidic chip operating at a high throughput of 10 000 blood cells per second with machine learning, enabling morphology-based identification and enumeration of aggregated platelets in a short period of time. By performing cell classification with machine learning, we differentiate aggregated platelets from single platelets and white blood cells with a high specificity and sensitivity of 96.6% for both. Our results indicate that the assay is potentially promising as predictive diagnosis and therapeutic monitoring of thrombotic disorders in clinical settings.

High-throughput, label-free, single-cell, microalgal lipid screening by machine-learning-equipped optofluidic time-stretch quantitative phase microscopy.

The development of reliable, sustainable, and economical sources of alternative fuels to petroleum is required to tackle the global energy crisis. One such alternative is microalgal biofuel, which is expected to play a key role in reducing the detrimental effects of global warming as microalgae absorb atmospheric CO2 via photosynthesis. Unfortunately, conventional analytical methods only provide population-averaged lipid amounts and fail to characterize a diverse population of microalgal cells with single-cell resolution in a non-invasive and interference-free manner. Here high-throughput label-free single-cell screening of lipid-producing microalgal cells with optofluidic time-stretch quantitative phase microscopy was demonstrated. In particular, Euglena gracilis, an attractive microalgal species that produces wax esters (suitable for biodiesel and aviation fuel after refinement), within lipid droplets was investigated. The optofluidic time-stretch quantitative phase microscope is based on an integration of a hydrodynamic-focusing microfluidic chip, an optical time-stretch quantitative phase microscope, and a digital image processor equipped with machine learning. As a result, it provides both the opacity and phase maps of every single cell at a high throughput of 10,000 cells/s, enabling accurate cell classification without the need for fluorescent staining. Specifically, the dataset was used to characterize heterogeneous populations of E. gracilis cells under two different culture conditions (nitrogen-sufficient and nitrogen-deficient) and achieve the cell classification with an error rate of only 2.15%. The method holds promise as an effective analytical tool for microalgae-based biofuel production. © 2017 International Society for Advancement of Cytometry.

High-Throughput Accurate Single-Cell Screening of Euglena gracilis with Fluorescence-Assisted Optofluidic Time-Stretch Microscopy.

The development of reliable, sustainable, and economical sources of alternative fuels is an important, but challenging goal for the world. As an alternative to liquid fossil fuels, algal biofuel is expected to play a key role in alleviating global warming since algae absorb atmospheric CO2 via photosynthesis. Among various algae for fuel production, Euglena gracilis is an attractive microalgal species as it is known to produce wax ester (good for biodiesel and aviation fuel) within lipid droplets. To date, while there exist many techniques for inducing microalgal cells to produce and accumulate lipid with high efficiency, few analytical methods are available for characterizing a population of such lipid-accumulated microalgae including E. gracilis with high throughout, high accuracy, and single-cell resolution simultaneously. Here we demonstrate high-throughput, high-accuracy, single-cell screening of E. gracilis with fluorescence-assisted optofluidic time-stretch microscopy-a method that combines the strengths of microfluidic cell focusing, optical time-stretch microscopy, and fluorescence detection used in conventional flow cytometry. Specifically, our fluorescence-assisted optofluidic time-stretch microscope consists of an optical time-stretch microscope and a fluorescence analyzer on top of a hydrodynamically focusing microfluidic device and can detect fluorescence from every E. gracilis cell in a population and simultaneously obtain its image with a high throughput of 10,000 cells/s. With the multi-dimensional information acquired by the system, we classify nitrogen-sufficient (ordinary) and nitrogen-deficient (lipid-accumulated) E. gracilis cells with a low false positive rate of 1.0%. This method holds promise for evaluating cultivation techniques and selective breeding for microalgae-based biofuel production.