Genetically predicted gut microbiota mediate the association between plasma lipidomics and primary sclerosing cholangitis.

BACKGROUND: Primary sclerosing cholangitis (PSC) is a complex disease with pathogenic mechanisms that remain to be elucidated. Previous observational studies with small sample sizes have reported associations between PSC, dyslipidemia, and gut microbiota dysbiosis. However, the causality of these associations is uncertain, and there has been no systematic analysis to date. METHODS: The datasets comprise data on PSC, 179 lipid species, and 412 gut microbiota species. PSC data (n = 14,890) were sourced from the International PSC Study Group, while the dataset pertaining to plasma lipidomics originated from a study involving 7174 Finnish individuals. Data on gut microbiota species were derived from the Dutch Microbiome Project study, which conducted a genome-wide association study involving 7738 participants. Furthermore, we employed a two-step Mendelian randomization (MR) analysis to quantify the proportion of the effect of gut microbiota-mediated lipidomics on PSC. RESULTS: Following a rigorous screening process, our MR analysis revealed a causal relationship between higher levels of gene-predicted Phosphatidylcholine (O-16:1_18:1) (PC O-16:1_18:1) and an increased risk of developing PSC (inverse variance-weighted method, odds ratio (OR) 1.30, 95% confidence interval (CI) 1.03-1.63). There is insufficient evidence to suggest that gene-predicted PSC impacts the levels of PC O-16:1_18:1 (OR 1.01, 95% CI 0.98-1.05). When incorporating gut microbiota data into the analysis, we found that Eubacterium rectale-mediated genetic prediction explains 17.59% of the variance in PC O-16:1_18:1 levels. CONCLUSION: Our study revealed a causal association between PC O-16:1_18:1 levels and PSC, with a minor portion of the effect mediated by Eubacterium rectale. This study aims to further explore the pathogenesis of PSC and identify promising therapeutic targets. For patients with PSC who lack effective treatment options, the results are encouraging.

NIR-activated electrospun nanodetonator dressing enhances infected diabetic wound healing with combined photothermal and nitric oxide-based gas therapy.

Diabetic wounds pose a challenge to healing due to increased bacterial susceptibility and poor vascularization. Effective healing requires simultaneous bacterial and biofilm elimination and angiogenesis stimulation. In this study, we incorporated polyaniline (PANI) and S-Nitrosoglutathione (GSNO) into a polyvinyl alcohol, chitosan, and hydroxypropyltrimethyl ammonium chloride chitosan (PVA/CS/HTCC) matrix, creating a versatile wound dressing membrane through electrospinning. The dressing combines the advantages of photothermal antibacterial therapy and nitric oxide gas therapy, exhibiting enduring and effective bactericidal activity and biofilm disruption against methicillin-sensitive Staphylococcus aureus, methicillin-resistant Staphylococcus aureus, and Escherichia coli. Furthermore, the membrane's PTT effect and NO release exhibit significant synergistic activation, enabling a nanodetonator-like burst release of NO through NIR irradiation to disintegrate biofilms. Importantly, the nanofiber sustained a uniform release of nitric oxide, thereby catalyzing angiogenesis and advancing cellular migration. Ultimately, the employment of this membrane dressing culminated in the efficacious amelioration of diabetic-infected wounds in Sprague-Dawley rats, achieving wound closure within a concise duration of 14 days. Upon applying NIR irradiation to the PVA-CS-HTCC-PANI-GSNO nanofiber membrane, it swiftly eradicates bacteria and biofilm within 5 min, enhancing its inherent antibacterial and anti-biofilm properties through the powerful synergistic action of PTT and NO therapy. It also promotes angiogenesis, exhibits excellent biocompatibility, and is easy to use, highlighting its potential in treating diabetic wounds.

Melatonin protects zebrafish pancreatic development and physiological rhythms from sodium propionate-induced disturbances via the hypothalamic-pituitary-thyroid axis.

BACKGROUND: The widespread use of sodium propionate as a preservative in food may affect public health. We aimed to assess the effects of sodium propionate on circadian rhythms and pancreatic development in zebrafish and the possible underlying mechanisms. RESULTS: In this experiment, we analyzed the relationship between circadian rhythms and pancreatic development and then revealed the role of the thyroid endocrine system in zebrafish. The results showed that sodium propionate interfered with the rhythmic behavior of zebrafish, and altered the expression of important rhythmic genes. Experimental data revealed that pancreatic morphology and developmental genes were altered after sodium propionate exposure. Additionally, thyroid hormone levels and key gene expression associated with the hypothalamic-pituitary-thyroid axis were significantly altered. Melatonin at a concentration of 1 µmol L-1, with a mild effect on zebrafish, observably alleviated sodium propionate-induced disturbances in circadian rhythms and pancreatic development, as well as regulating the thyroid system. CONCLUSION: Melatonin, while modulating the thyroid system, significantly alleviates sodium propionate-induced circadian rhythm disturbances and pancreatic developmental disorders. We further revealed the deleterious effects of sodium propionate as well as the potential therapeutic effects of melatonin on circadian rhythm, pancreatic development and the thyroid system. © 2024 Society of Chemical Industry.

Predicting rectal cancer prognosis from histopathological images and clinical information using multi-modal deep learning.

Objective: The objective of this study was to provide a multi-modal deep learning framework for forecasting the survival of rectal cancer patients by utilizing both digital pathological images data and non-imaging clinical data. Materials and methods: The research included patients diagnosed with rectal cancer by pathological confirmation from January 2015 to December 2016. Patients were allocated to training and testing sets in a randomized manner, with a ratio of 4:1. The tissue microarrays (TMAs) and clinical indicators were obtained. Subsequently, we selected distinct deep learning models to individually forecast patient survival. We conducted a scanning procedure on the TMAs in order to transform them into digital pathology pictures. Additionally, we performed pre-processing on the clinical data of the patients. Subsequently, we selected distinct deep learning algorithms to conduct survival prediction analysis using patients' pathological images and clinical data, respectively. Results: A total of 292 patients with rectal cancer were randomly allocated into two groups: a training set consisting of 234 cases, and a testing set consisting of 58 instances. Initially, we make direct predictions about the survival status by using pre-processed Hematoxylin and Eosin (H&E) pathological images of rectal cancer. We utilized the ResNest model to extract data from histopathological images of patients, resulting in a survival status prediction with an AUC (Area Under the Curve) of 0.797. Furthermore, we employ a multi-head attention fusion (MHAF) model to combine image features and clinical features in order to accurately forecast the survival rate of rectal cancer patients. The findings of our experiment show that the multi-modal structure works better than directly predicting from histopathological images. It achieves an AUC of 0.837 in predicting overall survival (OS). Conclusions: Our study highlights the potential of multi-modal deep learning models in predicting survival status from histopathological images and clinical information, thus offering valuable insights for clinical applications.

The m6A modification mediated-lncRNA POU6F2-AS1 reprograms fatty acid metabolism and facilitates the growth of colorectal cancer via upregulation of FASN.

BACKGROUND: Long noncoding RNAs (lncRNAs) have emerged as key players in tumorigenesis and tumour progression. However, the biological functions and potential mechanisms of lncRNAs in colorectal cancer (CRC) are unclear. METHODS: The novel lncRNA POU6F2-AS1 was identified through bioinformatics analysis, and its expression in CRC patients was verified via qRT-PCR and FISH. In vitro and in vivo experiments, such as BODIPY staining, Oil Red O staining, triglyceride (TAG) assays, and liquid chromatography mass spectrometry (LC-MS) were subsequently performed with CRC specimens and cells to determine the clinical significance, and functional roles of POU6F2-AS1. Biotinylated RNA pull-down, RIP, Me-RIP, ChIP, and patient-derived organoid (PDO) culture assays were performed to confirm the underlying mechanism of POU6F2-AS1. RESULTS: The lncRNA POU6F2-AS1 is markedly upregulated in CRC and associated with adverse clinicopathological features and poor overall survival in CRC patients. Functionally, POU6F2-AS1 promotes the growth and lipogenesis of CRC cells both in vitro and in vivo. Mechanistically, METTL3-induced m6A modification is involved in the upregulation of POU6F2-AS1. Furthermore, upregulated POU6F2-AS1 could tether YBX1 to the FASN promoter to induce transcriptional activation, thus facilitating the growth and lipogenesis of CRC cells. CONCLUSIONS: Our data revealed that the upregulation of POU6F2-AS1 plays a critical role in CRC fatty acid metabolism and might provide a novel promising biomarker and therapeutic target for CRC.

Three-in-One Peptide Prodrug with Targeting, Assembly and Release Properties for Overcoming Bacterium-Induced Drug Resistance and Potentiating Anti-Cancer Immune Response.

The presence of bacteria in tumor results in chemotherapeutic drug resistance and weakens the immune response in colorectal cancer. To overcome bacterium-induced chemotherapeutic drug resistance and potentiate antitumor immunity, herein a novel molecule Biotin-Lys(SA-Cip-OH)-Lys(SA-CPT)-Phe-Phe-Nap (Biotin-Cip-CPT-Nap) is rationally designed containing four functional motifs (i.e., a biotin motif for targeting, Phe-Phe(-Nap) motif for self-assembly, ciprofloxacin derivative (Cip-OH) motif for antibacterial effect, and camptothecin (CPT) motif for chemotherapy). Using the designed molecule, a novel strategy of intracellular enzymatic nanofiber formation and synergistic antibacterium-enhanced chemotherapy and immunotherapy is achieved. Under endocytosis mediated by highly expressed biotin receptor in colorectal cancer cell membrane and the catalysis of highly expressed carboxylesterase in the cytoplasm, this novel molecule can be transformed into Biotin-Nap, which self-assembled into nanofibers. Meanwhile, antibiotic Cip-OH and chemotherapeutic drug CPT are released, overcoming bacterium-induced drug resistance and enhancing the therapeutic efficacy of immunotherapy towards colorectal cancer. This work offers a feasible strategy for the design of novel multifunctional prodrugs to improve the efficiency of colorectal cancer treatment.

Injectable Hydrogel Delivery System with High Drug Loading for Prolonging Local Anesthesia.

Peripheral nerve block is performed for precise pain control and lesser side effects after surgery by reducing opioid consumption. Injectable hydrogel delivery systems with high biosafety and moisture content have good clinical application prospects for local anesthetic delivery. However, how to achieve high drug loading and long-term controlled release of water-soluble narcotic drugs remains a big challenge. In this study, heterogeneous microspheres and an injectable gel-matrix composite drug delivery system are designed in two steps. First, heterogeneous hydrogel microspheres loaded with ropivacaine (HMS-ROP) are prepared using a microfluidic chip and in situ alkalization. An injectable self-healing hydrogel matrix (Gel) is then prepared from modified carboxymethylcellulose (CMC-ADH) and oxidized hyaluronic acid (OHA). A local anesthetic delivery system, Gel/HMS-ROP/dexmedetomidine (DEX), with long-term retention and drug release in vivo is prepared by combining HMS-ROP and Gel/DEX. The drug loading of HMS-ROP reached 41.1%, with a drug release time of over 160 h in vitro, and sensory and motor blockade times in vivo of 48 and 36 h, respectively. In summary, the sequential release and synergistic analgesic effects of the two anesthetics are realized using core-shell microspheres, DEX, and an injectable gel, providing a promising strategy for long-acting postoperative pain management.

HES1 induces ITPR1-mediated autophagy to exert anti-metastatic effects in pituitary adenomas.

Background: Pituitary adenomas (PAs) are prevalent intracranial tumors necessitating a comprehensive exploration of their molecular intricacies. This study delved into the molecular interactions among HES1 (hairy and enhancer of split 1), ITPR1 (inositol 1,4,5-trisphosphate receptor, type 1), and autophagy to elucidate their contributions to PA progression. Methods: Our in-depth bioinformatics analysis identified ITPR1 as a central hub gene in the PA-associated dataset. It exhibited reduced expression in PA and held significant clinical diagnostic relevance. Motivated by this discovery, we investigated the consequences of ITPR1 overexpression, as well as the use of autophagy inhibitors 3-Methyladenine (3-MA) and Baf A1, while considering the transcriptional influence of HES1. Results: In vitro experiments utilizing PA cell lines revealed that ITPR1 overexpression significantly hindered tumorigenic activities. In contrast, both 3-MA and Baf A1 exacerbated these tumorigenic properties, confirmed by a decreased LC3 II/LC3 I ratio, indicative of autophagy inhibition. Intriguingly, the concurrent introduction of ITPR1 and these inhibitors mitigated these intensified effects, implying a tumor-suppressive role for ITPR1. Further investigations pinpoint HES1 as a potential upstream regulator of ITPR1 transcription. Silencing HES1 lead to reduced ITPR1 promoter activity, weakening the impact of ITPR1 overexpression on autophagy. This neutralized the ITPR1-mediated suppressions on PA cell activities, including proliferation, invasion, and migration. Conclusions: In summary, our research uncovered a complex regulatory interplay among HES1, ITPR1, and autophagy in the context of PA progression. These findings opened up promising avenues for novel therapeutic interventions targeting this intricate network to enhance PA treatment.

In Situ Monitoring of Non-Thermal Plasma Cleaning of Surfactant Encapsulated Nanoparticles.

Surfactants are widely used in the synthesis of nanoparticles, as they have a remarkable ability to direct their growth to obtain well-defined shapes and sizes. However, their post-synthesis removal is a challenge, and the methods used often result in morphological changes that defeat the purpose of the initial controlled growth. Moreover, after the removal of surfactants, the highly active surfaces of nanomaterials may undergo structural reconstruction by exposure to a different environment. Thus, ex situ characterization after air exposure may not reflect the effect of the cleaning methods. Here, combining X-ray photoelectron spectroscopy, in situ infrared reflection absorption spectroscopy, and environmental transmission electron microscopy measurements with CO probe experiments, we investigated different surfactant-removal methods to produce clean metallic Pt nanoparticles from surfactant-encapsulated ones. It was demonstrated that both ultraviolet-ozone (UV-ozone) treatment and room temperature O2 plasma treatment led to the formation of Pt oxides on the surface after the removal of the surfactant. On the other hand, when H2 was used for plasma treatment, both the Pt0 oxidation state and nanoparticle size distribution were preserved. In addition, H2 plasma treatment can reduce Pt oxides after O2-based treatments, resulting in metallic nanoparticles with clean surfaces. These findings provide a better understanding of the various options for surfactant removal from metal nanoparticles and point toward non-thermal plasmas as the best route if the integrity of the nanoparticle needs to be preserved.

CAMSAPs and nucleation-promoting factors control microtubule release from γ-TuRC.

γ-Tubulin ring complex (γ-TuRC) is the major microtubule-nucleating factor. After nucleation, microtubules can be released from γ-TuRC and stabilized by other proteins, such as CAMSAPs, but the biochemical cross-talk between minus-end regulation pathways is poorly understood. Here we reconstituted this process in vitro using purified components. We found that all CAMSAPs could bind to the minus ends of γ-TuRC-attached microtubules. CAMSAP2 and CAMSAP3, which decorate and stabilize growing minus ends but not the minus-end tracking protein CAMSAP1, induced microtubule release from γ-TuRC. CDK5RAP2, a γ-TuRC-interactor, and CLASP2, a regulator of microtubule growth, strongly stimulated γ-TuRC-dependent microtubule nucleation, but only CDK5RAP2 suppressed CAMSAP binding to γ-TuRC-anchored minus ends and their release. CDK5RAP2 also improved selectivity of γ-tubulin-containing complexes for 13- rather than 14-protofilament microtubules in microtubule-capping assays. Knockout and overexpression experiments in cells showed that CDK5RAP2 inhibits the formation of CAMSAP2-bound microtubules detached from the microtubule-organizing centre. We conclude that CAMSAPs can release newly nucleated microtubules from γ-TuRC, whereas nucleation-promoting factors can differentially regulate this process.

METTL14-mediated m6A epitranscriptomic modification contributes to chemotherapy-induced neuropathic pain by stabilizing GluN2A expression via IGF2BP2.

Epigenetics is a biological process that modifies and regulates gene expression, affects neuronal function, and contributes to pain. However, the mechanism by which epigenetics facilitates and maintains chronic pain is poorly understood. We aimed to determine whether N6-methyladenosine (m6A) specifically modified by methyltransferase-like 14 (METTL14) alters neuronal activity and governs pain by sensitizing the GluN2A subunit of the N-methyl-d-aspartate receptor (NMDAR) in the dorsal root ganglion (DRG) neurons in a model of chemotherapy-induced neuropathic pain (CINP). Using dot blotting, immunofluorescence, gain/loss-of-function, and behavioral assays, we found that m6A levels were upregulated in L4-L6 DRG neurons in CINP in a DBP/METTL14-dependent manner, which was also confirmed in human DRGs. Blocking METTL14 reduced m6A methylation and attenuated pain hypersensitivity. Mechanistically, METTL14-mediated m6A modification facilitated the synaptic plasticity of DRG neurons by enhancing the GluN2A subunit of NMDAR, and inhibiting METTL14 blocked this effect. In contrast, overexpression of METTL14 upregulated m6A modifications, enhanced presynaptic NMDAR activity in DRG neurons, and facilitated pain sensation. Our findings reveal a previously unrecognized mechanism of METTL14-mediated m6A modification in DRG neurons to maintain neuropathic pain. Targeting these molecules may provide a new strategy for pain treatment.

GAM-MDR: probing miRNA-drug resistance using a graph autoencoder based on random path masking.

MicroRNAs (miRNAs) are found ubiquitously in biological cells and play a pivotal role in regulating the expression of numerous target genes. Therapies centered around miRNAs are emerging as a promising strategy for disease treatment, aiming to intervene in disease progression by modulating abnormal miRNA expressions. The accurate prediction of miRNA-drug resistance (MDR) is crucial for the success of miRNA therapies. Computational models based on deep learning have demonstrated exceptional performance in predicting potential MDRs. However, their effectiveness can be compromised by errors in the data acquisition process, leading to inaccurate node representations. To address this challenge, we introduce the GAM-MDR model, which combines the graph autoencoder (GAE) with random path masking techniques to precisely predict potential MDRs. The reliability and effectiveness of the GAM-MDR model are mainly reflected in two aspects. Firstly, it efficiently extracts the representations of miRNA and drug nodes in the miRNA-drug network. Secondly, our designed random path masking strategy efficiently reconstructs critical paths in the network, thereby reducing the adverse impact of noisy data. To our knowledge, this is the first time that a random path masking strategy has been integrated into a GAE to infer MDRs. Our method was subjected to multiple validations on public datasets and yielded promising results. We are optimistic that our model could offer valuable insights for miRNA therapeutic strategies and deepen the understanding of the regulatory mechanisms of miRNAs. Our data and code are publicly available at GitHub:https://github.com/ZZCrazy00/GAM-MDR.

Silver oxide decorated urchin-like microporous organic polymer composites as versatile antibacterial organic coating materials.

Microporous organic polymers (MOPs) and metal oxide hybrid composites are considered valuable coating materials because of their versatility derived from the synergistic combination of MOPs' inherent dispersibility and the distinctive properties of metal oxides. In this study, we present the synthesis of sea-urchin-like MOPs hybridised with silver oxide nanoparticles (Ag2O NPs) to fabricate antibacterial composites suitable for potential antibacterial coating applications. Ag2O NP-decorated urchin-like MOPs (Ag2O@UMOPs) were synthesised by employing a combination of two methods: a one-pot Lewis acid-base interaction-mediated self-assembly and a straightforward impregnation process. The as-prepared Ag2O@UMOPs demonstrated high antibacterial efficacy against both E. coli (G-) and S. aureus (G+). The antibacterial mechanism of Ag2O@UMOPs mainly involved the synergistic effects of accumulation of Ag2O@UMOPs, the release of Ag+ ions, and the generation of reactive oxygen species. The exceptional processability and biosafety of Ag2O@UMOPs make them ideal organic coating materials for convenient application on various substrates. These remarkable features of Ag2O@UMOPs provide an effective platform for potential antibacterial applications in biological sciences.

Computational design of an imine reductase: mechanism-guided stereoselectivity reversion and interface stabilization.

Imine reductases (IREDs) are important biocatalysts in the asymmetric synthesis of chiral amines. However, a detailed understanding of the stereocontrol mechanism of IRED remains incomplete, making the design of IRED for producing the desired amine enantiomers challenging. In this study, we investigated the stereoselective catalytic mechanism and designed an (R)-stereoselective IRED from Paenibacillus mucilaginosus (PmIR) using pharmaceutically relevant 2-aryl-substituted pyrrolines as substrates. A putative mechanism for controlling stereoselectivity was proposed based on the crucial role of electrostatic interactions in controlling iminium cation orientation and employed to achieve complete inversion of stereoselectivity in PmIR using computational design. The variant PmIR-Re (Q138M/P140M/Y187E/Q190A/D250M/R251N) exhibited opposite (S)-stereoselectivity, with >96% enantiomeric excess (ee) towards tested 2-aryl-substituted pyrrolines. Computational tools were employed to identify stabilizing mutations at the interface between the two subunits. The variant PmIR-6P (P140A/Q190S/R251N/Q217E/A257R/T277M) showed a nearly 5-fold increase in activity and a 12 °C increase in melting temperature. The PmIR-6P successfully produced (R)-2-(2,5-difluorophenyl)-pyrrolidine, a key chiral pharmaceutical intermediate, at a concentration of 400 mM with an ee exceeding 99%. This study provides insight into the stereocontrol elements of IREDs and demonstrates the potential of computational design for tailored stereoselectivity and thermal stability.

Ferroelectric FET-based context-switching FPGA enabling dynamic reconfiguration for adaptive deep learning machines.

Field programmable gate array (FPGA) is widely used in the acceleration of deep learning applications because of its reconfigurability, flexibility, and fast time-to-market. However, conventional FPGA suffers from the trade-off between chip area and reconfiguration latency, making efficient FPGA accelerations that require switching between multiple configurations still elusive. Here, we propose a ferroelectric field-effect transistor (FeFET)-based context-switching FPGA supporting dynamic reconfiguration to break this trade-off, enabling loading of arbitrary configuration without interrupting the active configuration execution. Leveraging the intrinsic structure and nonvolatility of FeFETs, compact FPGA primitives are proposed and experimentally verified. The evaluation results show our design shows a 63.0%/74.7% reduction in a look-up table (LUT)/connection block (CB) area and 82.7%/53.6% reduction in CB/switch box power consumption with a minimal penalty in the critical path delay (9.6%). Besides, our design yields significant time savings by 78.7 and 20.3% on average for context-switching and dynamic reconfiguration applications, respectively.

METTL14 contributes to acute lung injury by stabilizing NLRP3 expression in an IGF2BP2-dependent manner.

Acute lung injury (ALI) as well as its more severe form, acute respiratory distress syndrome (ARDS), frequently leads to an uncontrolled inflammatory response. N6-methyladenosine (m6A) modification was associated with the progression of several inflammatory diseases. However, the role of methyltransferase-like 14 (METTL14)-mediated m6A methylation in ALI/ARDS remains unclear. Here, we reported an increase in overall expression levels of m6A and METTL14 in circulating monocyte-derived macrophages recruited to the lung following ALI, which is correlated with the severity of lung injury. We further demonstrated the critical function of METTL14 in activating NOD-like receptor pyrin domain-containing protein 3 (NLRP3) inflammasome in vitro and in mouse models of ALI/ARDS, and validated NLRP3 as the downstream target of METTL14 by the m6A RNA immunoprecipitation (MeRIP) and RIP assays. Mechanistically, METTL14-methylated NLRP3 transcripts were subsequently recognized by insulin-like growth factor 2 mRNA-binding protein 2 (IGF2BP2), an m6A reader, which stabilized NLRP3 mRNA. Furthermore, we observed that IGF2BP2 knockdown diminished LPS-induced ALI in mice by downregulating NLRP3 expression. In summation, our study revealed that the molecular mechanism underlying the pathogenesis of ALI/ARDS involves METTL14-mediated activation of NLRP3 inflammasome in an IGF2BP2 dependent manner, thereby demonstrating the potential of METTL14 and IGF2BP2 as promising biomarkers and therapeutic targets for ALI/ARDS treatment.

Metallo-supramolecular branched polymer protects particles from air-water interface in single-particle cryo-electron microscopy.

Recent technological breakthroughs in single-particle cryo-electron microscopy (cryo-EM) enable rapid atomic structure determination of biological macromolecules. A major bottleneck in the current single particle cryo-EM pipeline is the preparation of good quality frozen cryo-EM grids, which is mostly a trial-and-error process. Among many issues, preferred particle orientation and sample damage by air-water interface (AWI) are common practical problems. Here we report a method of applying metallo-supramolecular branched polymer (MSBP) in the cryo-sample preparation for high-resolution single-particle cryo-EM. Our data shows that MSBP keeps a majority of particles away from air-water interface and mitigates preferred orientation as verified by the analyses of apoferritin, hemagglutinin) trimer and various sample proteins. The use of MSBP is a simple method to improve particle distribution for high-resolution structure determination in single-particle cryo-EM.

Embedding security into ferroelectric FET array via in situ memory operation.

Non-volatile memories (NVMs) have the potential to reshape next-generation memory systems because of their promising properties of near-zero leakage power consumption, high density and non-volatility. However, NVMs also face critical security threats that exploit the non-volatile property. Compared to volatile memory, the capability of retaining data even after power down makes NVM more vulnerable. Existing solutions to address the security issues of NVMs are mainly based on Advanced Encryption Standard (AES), which incurs significant performance and power overhead. In this paper, we propose a lightweight memory encryption/decryption scheme by exploiting in-situ memory operations with negligible overhead. To validate the feasibility of the encryption/decryption scheme, device-level and array-level experiments are performed using ferroelectric field effect transistor (FeFET) as an example NVM without loss of generality. Besides, a comprehensive evaluation is performed on a 128 × 128 FeFET AND-type memory array in terms of area, latency, power and throughput. Compared with the AES-based scheme, our scheme shows ~22.6×/~14.1× increase in encryption/decryption throughput with negligible power penalty. Furthermore, we evaluate the performance of our scheme over the AES-based scheme when deploying different neural network workloads. Our scheme yields significant latency reduction by 90% on average for encryption and decryption processes.

An investigation of the risk factors of chronic obstructive pulmonary disease in natural population-based cohorts in China - a nested case-control study.

Background: Chronic obstructive pulmonary disease (COPD) has become one of the most significant chronic diseases in China. According to conventional wisdom, smoking is the pathogenic factor. However, current research indicates that the pathophysiology of COPD may be associated with prior respiratory system events (e.g., childhood hospitalization for pneumonia, chronic bronchitis) and environmental exposure (e.g., dust from workplace, indoor combustion particles). Dyspnea, persistent wheezing, and other respiratory symptoms further point to the need for pulmonary function tests in this population. Reducing the burden of chronic diseases in China requires a thorough understanding of the various factors that influence the occurrence of COPD. Methods: Using a cohort from the natural population, this study used nested case-control analysis. We carried out a number of researches, including questionnaire surveys and pulmonary function testing, in the Northwest and Southeast cohorts of China between 2014 and 2021. After removing any variations in the baseline data between patients and control subjects using propensity score matching analysis, the risk factors were examined using univariate or multivariate regression. Result: It was discovered that prior history of chronic bronchitis, long-term wheezing symptoms, and environmental exposure-including smoking and biofuel combustion-were risk factors for COPD. Dyspnea, symptoms of mobility limitation, organic matter, and a history of hospitalization for pneumonia at an early age were not significant in the clinical model but their incidence in COPD group is higher than that in healthy population. Discussion: COPD screening effectiveness can be increased by looking for individuals with chronic respiratory symptoms. Smokers should give up as soon as they can, and families that have been exposed to biofuels for a long time should convert to clean energy or upgrade their ventilation. Individuals who have previously been diagnosed with emphysema and chronic bronchitis ought to be extra mindful of the prevention or advancement of COPD.