Assessing and Optimizing Large Language Models on Spondyloarthritis Multi-Choice Question Answering: Protocol for Enhancement and Assessment.

BACKGROUND: Spondyloarthritis (SpA), a chronic inflammatory disorder, predominantly impacts the sacroiliac joints and spine, significantly escalating the risk of disability. SpA's complexity, as evidenced by its diverse clinical presentations and symptoms that often mimic other diseases, presents substantial challenges in its accurate diagnosis and differentiation. This complexity becomes even more pronounced in nonspecialist health care environments due to limited resources, resulting in delayed referrals, increased misdiagnosis rates, and exacerbated disability outcomes for patients with SpA. The emergence of large language models (LLMs) in medical diagnostics introduces a revolutionary potential to overcome these diagnostic hurdles. Despite recent advancements in artificial intelligence and LLMs demonstrating effectiveness in diagnosing and treating various diseases, their application in SpA remains underdeveloped. Currently, there is a notable absence of SpA-specific LLMs and an established benchmark for assessing the performance of such models in this particular field. OBJECTIVE: Our objective is to develop a foundational medical model, creating a comprehensive evaluation benchmark tailored to the essential medical knowledge of SpA and its unique diagnostic and treatment protocols. The model, post-pretraining, will be subject to further enhancement through supervised fine-tuning. It is projected to significantly aid physicians in SpA diagnosis and treatment, especially in settings with limited access to specialized care. Furthermore, this initiative is poised to promote early and accurate SpA detection at the primary care level, thereby diminishing the risks associated with delayed or incorrect diagnoses. METHODS: A rigorous benchmark, comprising 222 meticulously formulated multiple-choice questions on SpA, will be established and developed. These questions will be extensively revised to ensure their suitability for accurately evaluating LLMs' performance in real-world diagnostic and therapeutic scenarios. Our methodology involves selecting and refining top foundational models using public data sets. The best-performing model in our benchmark will undergo further training. Subsequently, more than 80,000 real-world inpatient and outpatient cases from hospitals will enhance LLM training, incorporating techniques such as supervised fine-tuning and low-rank adaptation. We will rigorously assess the models' generated responses for accuracy and evaluate their reasoning processes using the metrics of fluency, relevance, completeness, and medical proficiency. RESULTS: Development of the model is progressing, with significant enhancements anticipated by early 2024. The benchmark, along with the results of evaluations, is expected to be released in the second quarter of 2024. CONCLUSIONS: Our trained model aims to capitalize on the capabilities of LLMs in analyzing complex clinical data, thereby enabling precise detection, diagnosis, and treatment of SpA. This innovation is anticipated to play a vital role in diminishing the disabilities arising from delayed or incorrect SpA diagnoses. By promoting this model across diverse health care settings, we anticipate a significant improvement in SpA management, culminating in enhanced patient outcomes and a reduced overall burden of the disease. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/57001.

2D Ferroionics: Conductive Switching Mechanisms and Transition Boundaries in Van der Waals Layered Material CuInP2 S6.

The recently unfolded ferroionic phenomena in 2D van der Waals (vdW) copper-indium-thiophosphate (CuInP2 S6 or CIPS) have received widespread interest as they allow for dynamic control of conductive switching properties, which are appealing in the paradigm-shift computing. The intricate couplings between ferroelectric polarization and ionic conduction in 2D vdW CIPS facilitate the manipulation and dynamic control of conductive behaviors. However, the complex interplays and underlying mechanisms are not yet fully explored and understood. Here, by investigating polarization switching and ionic conduction in the temperature and applied electric field domains, it is discovered that the conducting mechanisms of CIPS can be divided into four distinctive states (or modes) with transitional boundaries, depending on the dynamics of Cu ions in the material. Further, it demonstrates that dynamically-tunable synaptic responsive behavior can be well implemented by governing the working-state transition. This research provides an in-depth, quantitative understanding of the complex phenomena of conductive switching in 2D vdW CIPS with coexisting ferroelectric order and ionic disorder. The developed insights in this work lay the ground for implementing high-performance, function-enriched devices for information processing, data storage, and neuromorphic computing based on the 2D ferroionic material systems.

Current crowding in graphene-silicon schottky diodes.

The performance of the Graphene/Si (Gr/Si) Schottky interface and its potential in future electronics strongly rely on the quality of interconnecting contacts with external circuitry. In this work, we investigate the dominating and limiting factors of Gr/Si interfaces designed for high light absorption, paying particular attention to the nature of the contact failure under high electrostatic discharge (ESD) conditions. Our findings indicate that severe current crowding at contact edges of the graphene is the dominating factor for the device breakdown. Material degradation and electrical breakdown are systematically analyzed by atomic force, Raman, scanning electron, and energy-dispersive x-ray spectroscopies. This work enlists the robustness and limitations of Gr/Si junction in photodiode architecture under high ESD conditions that can be used as general guidelines for 2D-3D electronic and optoelectronic devices.

Introduction of defects in hexagonal boron nitride for vacancy-based 2D memristors.

Two-dimensional (2D) materials have become potential resistive switching (RS) layers to prepare emerging non-volatile memristors. The atomically thin thickness and the highly controllable defect density contribute to the construction of ultimately scaled memory cells with stable switching behaviors. Although the conductive bridge random-access memory based on 2D hexagonal boron nitride has been widely studied, the realization of RS completely relying on vacancies in 2D materials has performance superiority. Here, we synthesize carbon-doped h-BN (C-h-BN) with a certain number of defects by controlling the weight percentage of carbon powder in the source. These defects can form a vacancy-based conductive filament under an applied electric field. The memristor displays bipolar non-volatile memory with a low SET voltage of 0.85 V and shows a long retention time of up to 104 s at 120 °C. The response times of the SET and RESET process are less than 80 ns and 240 ns, respectively. The current mapping by conductive atomic force microscopy demonstrates the electric-field-induced current tunneling from defective sites of the C-h-BN flake, revealing the defect-based RS in the C-h-BN memristor. Moreover, C-h-BN with excellent flexibility can be applied to wearable devices, maintaining stable RS performance in a variety of bending environments and after multiple bending cycles. The vacancy-based 2D memristor provides a new strategy for developing ultra-scaled memory units with high controllability.

Multi-Stimuli-Responsive Synapse Based on Vertical van der Waals Heterostructures.

Brain-inspired intelligent systems demand diverse neuromorphic devices beyond simple functionalities. Merging biomimetic sensing with weight-updating capabilities in artificial synaptic devices represents one of the key research focuses. Here, we report a multiresponsive synapse device that integrates synaptic and optical-sensing functions. The device adopts vertically stacked graphene/h-BN/WSe2 heterostructures, including an ultrahigh-mobility readout layer, a weight-control layer, and a dual-stimuli-responsive layer. The unique structure endows synapse devices with excellent synaptic plasticity, short response time (3 µs), and excellent optical responsivity (105 A/W). To demonstrate the application in neuromorphic computing, handwritten digit recognition was simulated based on an unsupervised spiking neural network (SNN) with a precision of 90.89%, well comparable with the state-of-the-art results. Furthermore, multiterminal neuromorphic devices are demonstrated to mimic dendritic integration and photoswitching logic. Different from other synaptic devices, the research work validates multifunctional integration in synaptic devices, supporting the potential fusion of sensing and self-learning in neuromorphic networks.

T-G-A Deficiency Pattern in Protein-Coding Genes and Its Potential Reason.

If a stop codon appears within one gene, then its translation will be terminated earlier than expected. False folding of premature protein will be adverse to the host; hence, all functional genes would tend to avoid the intragenic stop codons. Therefore, we hypothesize that there will be less frequency of nucleotides corresponding to stop codons at each codon position of genes. Here, we validate this inference by investigating the nucleotide frequency at a large scale and results from 19,911 prokaryote genomes revealed that nucleotides coinciding with stop codons indeed have the lowest frequency in most genomes. Interestingly, genes with three types of stop codons all tend to follow a T-G-A deficiency pattern, suggesting that the property of avoiding intragenic termination pressure is the same and the major stop codon TGA plays a dominant role in this effect. Finally, a positive correlation between the TGA deficiency extent and the base length was observed in start-experimentally verified genes of Escherichia coli (E. coli). This strengthens the proof of our hypothesis. The T-G-A deficiency pattern observed would help to understand the evolution of codon usage tactics in extant organisms.

The phyllosphere microbiome shifts toward combating melanose pathogen.

BACKGROUND: Plants can recruit beneficial microbes to enhance their ability to defend against pathogens. However, in contrast to the intensively studied roles of the rhizosphere microbiome in suppressing plant pathogens, the collective community-level change and effect of the phyllosphere microbiome in response to pathogen invasion remains largely elusive. RESULTS: Here, we integrated 16S metabarcoding, shotgun metagenomics and culture-dependent methods to systematically investigate the changes in phyllosphere microbiome between infected and uninfected citrus leaves by Diaporthe citri, a fungal pathogen causing melanose disease worldwide. Multiple microbiome features suggested a shift in phyllosphere microbiome upon D. citri infection, highlighted by the marked reduction of community evenness, the emergence of large numbers of new microbes, and the intense microbial network. We also identified the microbiome features from functional perspectives in infected leaves, such as enriched microbial functions for iron competition and potential antifungal traits, and enriched microbes with beneficial genomic characteristics. Glasshouse experiments demonstrated that several bacteria associated with the microbiome shift could positively affect plant performance under D. citri challenge, with reductions in disease index ranging from 65.7 to 88.4%. Among them, Pantoea asv90 and Methylobacterium asv41 identified as "recruited new microbes" in the infected leaves, exhibited antagonistic activities to D. citri both in vitro and in vivo, including inhibition of spore germination and/or mycelium growth. Sphingomonas spp. presented beneficial genomic characteristics and were found to be the main contributor for the functional enrichment of iron complex outer membrane receptor protein in the infected leaves. Moreover, Sphingomonas asv20 showed a stronger suppression ability against D. citri in iron-deficient conditions than iron-sufficient conditions, suggesting a role of iron competition during their antagonistic action. CONCLUSIONS: Overall, our study revealed how phyllosphere microbiomes differed between infected and uninfected citrus leaves by melanose pathogen, and identified potential mechanisms for how the observed microbiome shift might have helped plants cope with pathogen pressure. Our findings provide novel insights into understanding the roles of phyllosphere microbiome responses during pathogen challenge. Video abstract.

Improvements on sampling of point spread function in optical transfer function measurement.

Point spread function (PSF), which is the intensity distribution of optical system impulse response and usually acquired by imaging a single pinhole in experiment, can characterize the quality of optical imaging system. Faithful recording of the two-dimensional intensity distribution of PSF is key for accurate measurement of optical transfer function (OTF), however distortions in recorded PSF can be easily caused by a large sampling interval and the electronic noise of the detector. Under a given sampling interval, the position-phase difference between pixels and intensity signals can change the intensity distribution of acquired PSF remarkably, making the computed OTF or MTF (modulation transfer function) error prone. Aiming at problems existing in pinhole based MTF measurement methods, this paper developed a new method with underline physics similar to that of slanted edge method to realize sub-pixel sampling of PSF intensity by using accurate non-integer up-sampling matrix of separate binary pixels and applying random patterns shown on digital micro-mirror device (DMD) as target. Numerical simulations show that improvement on the discrete sampling of point spread function with this method is very helpful to improve anti-noise robustness and the accuracy of optical transfer function measurement.

Anti-CRISPRdb v2.2: an online repository of anti-CRISPR proteins including information on inhibitory mechanisms, activities and neighbors of curated anti-CRISPR proteins.

We previously released the Anti-CRISPRdb database hosting anti-CRISPR proteins (Acrs) and associated information. Since then, the number of known Acr families, types, structures and inhibitory activities has accumulated over time, and Acr neighbors can be used as a candidate pool for screening Acrs in further studies. Therefore, we here updated the database to include the new available information. Our newly updated database shows several improvements: (i) it comprises more entries and families because it includes both Acrs reported in the most recent literatures and Acrs obtained via performing homologous alignment; (ii) the prediction of Acr neighbors is integrated into Anti-CRISPRdb v2.2, and users can identify novel Acrs from these candidates; and (iii) this version includes experimental information on the inhibitory strength and stage for Acr-Cas/Acr-CRISPR pairs, motivating the development of tools for predicting specific inhibitory abilities. Additionally, a parameter, the rank of codon usage bias (CUBRank), was proposed and provided in the new version, which showed a positive relationship with predicted result from AcRanker; hence, it can be used as an indicator for proteins to be Acrs. CUBRank can be used to estimate the possibility of genes occurring within genome island-a hotspot hosting potential genes encoding Acrs. Based on CUBRank and Anti-CRISPRdb, we also gave the first glimpse for the emergence of Acr genes (acrs). DATABASE URL: http://guolab.whu.edu.cn/anti-CRISPRdb.

Recognition of Upper Limb Action Intention Based on IMU.

Using motion information of the upper limb to control the prosthetic hand has become a hotspot of current research. The operation of the prosthetic hand must also be coordinated with the user's intention. Therefore, identifying action intention of the upper limb based on motion information of the upper limb is key to controlling the prosthetic hand. Since a wearable inertial sensor bears the advantages of small size, low cost, and little external environment interference, we employ an inertial sensor to collect angle and angular velocity data during movement of the upper limb. Aiming at the action classification for putting on socks, putting on shoes and tying shoelaces, this paper proposes a recognition model based on the Dynamic Time Warping (DTW) algorithm of the motion unit. Based on whether the upper limb is moving, the complete motion data are divided into several motion units. Considering the delay associated with controlling the prosthetic hand, this paper only performs feature extraction on the first motion unit and the second motion unit, and recognizes action on different classifiers. The experimental results reveal that the DTW algorithm based on motion unit bears a higher recognition rate and lower running time. The recognition rate reaches as high as 99.46%, and the average running time measures 8.027 ms. In order to enable the prosthetic hand to understand the grasping intention of the upper limb, this paper proposes a Generalized Regression Neural Network (GRNN) model based on 10-fold cross-validation. The motion state of the upper limb is subdivided, and the static state is used as the sign of controlling the prosthetic hand. This paper applies a 10-fold cross-validation method to train the neural network model to find the optimal smoothing parameter. In addition, the recognition performance of different neural networks is compared. The experimental results show that the GRNN model based on 10-fold cross-validation exhibits a high accuracy rate, capable of reaching 98.28%. Finally, the two algorithms proposed in this paper are implemented in an experiment of using the prosthetic hand to reproduce an action, and the feasibility and practicability of the algorithm are verified by experiment.

Iterative reconstruction method for the accurate measurement of optical transfer function.

An iterative computation method was proposed to accurately reconstruct the optical transfer function (OTF) of an imaging lens from a series of recorded images of different patterns displayed on a digital micromirror device (DMD). Since several tens of recorded images are adopted in combination, the measurement noise is remarkably reduced in comparison with the conventional measurement method using a point object, and quite high measurement accuracy is reached by taking the known shape of each tiny mirror of the DMD into computation. While theoretical analysis is demonstrated, the validity of this proposed method is verified both numerically and experimentally.

[Research Status and Hot Trends in Atherosclerosis Genomics between 2010 and 2019].

Objective To analyze the research status,hotspots,and frontiers of atherosclerosis genomics from 2010 to 2019.Methods CiteSpace software was used to conduct data statistics and visual analysis on countries,institutions,authors,journals,co-cited papers,and keywords of the related papers published in the Web of Science from 2010 to 2019.Results A total of 1021 papers in English were included,and the annual number of publications generally showed an upward trend.The knowledge base in the research of atherosclerosis mostly focused on the genetic risk sites and biomarkers for coronary artery diseases such as coronary heart disease,myocardial infarction,and dyslipidemia.The related journals mainly involved the fields of molecular biology,biology,genetics,immunology,medicine,pharmacy,and clinical medicine.The latest research in atherosclerosis concentrated on genome-wide association study,DNA methylation,microRNA,messenger RNA and so on.The research frontiers involved long noncoding RNA,DNA methylation,and immune metabolism.Conclusion The studies in atherosclerotic genomics have gradually increased.

The Utility of Diffusion and Perfusion Magnetic Resonance Imaging in Target Delineation of High-Grade Gliomas.

BACKGROUND: The tumor volume of high-grade glioma (HGG) after surgery is usually determined by contrast-enhanced MRI (CE-MRI), but the clinical target volume remains controversial. Functional magnetic resonance imaging (multimodality MRI) techniques such as magnetic resonance perfusion-weighted imaging (PWI) and diffusion-tensor imaging (DTI) can make up for CE-MRI. This study explored the survival outcomes and failure patterns of patients with HGG by comparing the combination of multimodality MRI and CE-MRI imaging with CE-MRI alone. METHODS: 102 patients with postoperative HGG between 2012 and 2016 were included. 50 were delineated based on multimodality MRI (PWI, DTI) and CE-MRI (enhanced T1), and the other 52 were delineated based on CE-MRI as control. RESULTS: The median survival benefit was 6 months. The 2-year overall survival, progression-free survival, and local-regional control rates were 48% vs. 25%, 42% vs. 13.46%, and 40% vs. 13.46% for the multimodality MRI and CE-MRI cohorts, respectively. The two cohorts had similar rates of disease progression and recurrence but different proportions of failure patterns. The univariate analysis shows that characteristics of patients such as combined with epilepsy, the dose of radiotherapy, the selection of MRI were significant influence factors for 2-year overall survival. However, in multivariate analyses, only the selection of MRI was an independent significant predictor of overall survival. CONCLUSIONS: This study was the first to explore the clinical value of multimodality MRI in the delineation of radiotherapy target volume for HGG. The conclusions of the study have positive reference significance to the combination of multimodality MRI and CE-MRI in guiding the delineation of the radiotherapy target area for HGG patients.

Single-electron detection utilizing coupled nonlinear microresonators.

Since the discovery of the electron, the accurate detection of electrical charges has been a dream of the scientific community. Owing to some remarkable advantages, micro/nanoelectromechanical system-based resonators have been used to design electrometers with excellent sensitivity and resolution. Here, we demonstrate a novel ultrasensitive charge detection method utilizing nonlinear coupling in two micromechanical resonators. We achieve single-electron charge detection with a high resolution up to 0.197 ± 0.056 e / Hz at room temperature. Our findings provide a simple strategy for measuring electron charges with extreme accuracy.

Effects of Photoperiod on Acetaminophen-Induced Hepatotoxicity in Mice.

PURPOSE: Acetaminophen (APAP) is a clinically popular analgesic and antipyretic drug, but excessive APAP can cause fatal hepatotoxicity. Many factors affect the degree of APAP-induced liver injury. This study aimed to investigate how circadian rhythm affects the development of APAP-induced hepatotoxicity and to clarify the roles of photoperiod and dietary rhythm on APAP-induced hepatotoxicity in mice. METHODS: APAP-induced hepatotoxicity models were established by intraperitoneal injection of APAP (400 mg/kg) to mice. The mice were then divided into three treatment groups: normal diet, reversed diet, and reversed photoperiod. RESULTS: More severe liver injury was observed at zeitgeber time 12 (ZT12) than at zeitgeber time 0 (ZT0) in all treatment groups, suggesting that photoperiod played a critical role in APAP-induced liver injury. We observed a change in the expression of the circadian gene Per2, which may be responsible for regulation of liver injury by photoperiod. Our results showed negligible change in Per2 expression with diet reversion, whereas Cry1, Cry2, and Dbp expressions were more highly affected by diet reversion than was Per2 expression. Downstream effects including liver enzyme expression, GSH level, and inflammation factors were also examined to identify the mechanism of liver injury. The results indicated that the circadian gene Per2 participated in APAP biometabolism by regulating the expression of Cyp2e1, which may explain the more severe hepatotoxicity at ZT12 than at ZT0. CONCLUSION: APAP-induced hepatotoxicity can be mediated by photoperiod through the circadian gene Per2, suggesting that medicines containing APAP should be administered not only with food but also according to the appropriate photoperiod.

Microbial communities and soil chemical features associated with commercial production of the medicinal mushroom Ganoderma lingzhi in soil.

Crop production, including mushroom farming, may cause significant changes to the underlying substrates which in turn, can influence crop quality and quantity during subsequent years. Here in this study, we analyzed the production of the medicinal mushroom Ganoderma lingzhi and the associated soil microbial communities and soil chemical features over 24 months from April 2015 to April 2017. This Basidiomycete mushroom, known as Lingzhi in China, is commonly found on dead trees and wood logs in temperate and subtropical forests. Its economic and medicinal importance have propelled the development of a diversity of cultivation methods. The dominant method uses wood logs as the main substrate, which after colonization by Lingzhi mycelia, are buried in the soil to induce fruiting. The soil microbial communities over the 24 months were analyzed using the Illumina HiSeq platform targeting a portion of the bacterial 16S rRNA gene and the fungal internal transcribed spacer 1 (ITS1). Overall, a significant reduction of Lingzhi yield was observed over our experimentation period. Interestingly, temporal changes in soil microbial compositions were detected during the 24 months, with the fungal community showing more changes than that of bacteria in terms of both species richness and the relative abundance of several dominant species after each fruiting. The soil chemical features also showed significant changes, with decreasing soil nitrogen and phosphorus concentrations and increasing soil pH and iron content after each fruiting. We discuss the implications of our results in sustainable Lingzhi production in soil.

Metabarcoding reveals differences in fungal communities between unflooded versus tidal flat soil in coastal saline ecosystem.

In the saline-affected ecosystem, fungi have huge potential to promote growth, induce disease resistance and enhance tolerance against salt-stress of host plants. Since areas of plowland are gradually decreasing, the reclamation of coastal saline lands could play a crucial role in maintaining agricultural productivity and crop security globally. Therefore, it is of great significance to explore the fungal diversity in the coastal saline ecosystem. Here, we collected saline soil samples from unflooded areas and tidal flat areas, the two typical distinct landforms in coastal saline ecosystems, and used ITS metabarcoding to depict the diversity of fungal communities. We found that fungal species evenness had a remarkably higher variation from the tidal flat compared to unflooded soil samples. Furthermore, we also confirmed that the fungal niches differentiation reports in the coastal saline ecosystem. Our ITS based DNA sequencing revealed that both unflooded and tidal flat soil were mainly composed of amplicon sequence variants (ASVs) belonging to Ascomycota (93.43% and 86.91% respectively). Based on our findings, understanding the associations and distinctions of fungal microbiome between unflooded soil and tidal flat could provide the basis for the development of reclamation in coastal saline lands.

CasLocusAnno: a web-based server for annotating cas loci and their corresponding (sub)types.

In prokaryotes, Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR) and CRISPR-associated protein (Cas) systems constitute adaptive immune systems against mobile genetic elements (MGEs). Here, we introduce the Markov cluster algorithm (MCL) to Makarova et al.'s method in order to select a more reasonable profile. Additionally, our new Maximum Continuous Cas Subcluster (MCCS) method helps identification of tightly clustered loci. The comparison with two other commonly used programs shows that the method could identify Cas proteins with higher accuracy and lower Additional Prediction Rate (APR). Moreover, we developed a web-based server, CasLocusAnno (http://cefg.uestc.cn/CasLocusAnno), capable of annotating Cas proteins, cas loci and their (sub)types less than ~ 28 s following the whole proteome sequence submission. Its standalone version can be downloaded at https://github.com/RiversDong/CasLocusAnno.

MiR-140 modulates the inflammatory responses of Mycobacterium tuberculosis-infected macrophages by targeting TRAF6.

This study aimed to examine miR-140 expression in clinical samples from tuberculosis (TB) patients and to explore the molecular mechanisms of miR-140 in host-bacterial interactions during Mycobacterium tuberculosis (M tb) infections. The miR-140 expression and relevant mRNA expression were detected by quantitative real-time PCR (qRT-PCR); the protein expression levels were analysed by ELISA and western blot; M tb survival was measured by colony formation unit assay; potential interactions between miR-140 and the 3' untranslated region (UTR) of tumour necrosis factor receptor-associated factor 6 (TRAF6) was confirmed by luciferase reporter assay. MiR-140 was up-regulated in the human peripheral blood mononuclear cells (PBMCs) from TB patients and in THP-1 and U937 cells with M tb infection. Overexpression of miR-140 promoted M tb survival; on the other hand, miR-140 knockdown attenuated M tb survival. The pro-inflammatory cytokines including interleukin 6, tumour necrosis-α, interleukin-1ß and interferon-γ were enhanced by M tb infection in THP-1 and U937 cells. MiR-140 overexpression reduced these pro-inflammatory cytokines levels in THP-1 and U937 cells with M tb infection; while knockdown of miR-140 exerted the opposite actions. TRAF6 was identified to be a downstream target of miR-140 and was negatively modulated by miR-140. TRAF6 overexpression increased the pro-inflammatory cytokines levels and partially restored the suppressive effects of miR-140 overexpression on pro-inflammatory cytokines levels in THP-1 and U937 cells with M tb infection. In conclusion, our results implied that miR-140 promoted M tb survival and reduced the pro-inflammatory cytokines levels in macrophages with M tb infection partially via modulating TRAF6 expression.

MicroRNA-125b inhibits cell proliferation and induces cell apoptosis in esophageal squamous cell carcinoma by targeting BMF.

MicroRNAs (miRNAs) have been reported to regulate the expression of genes by suppressing translation or facilitating mRNA decay. Their expression regulates a wide variety of cellular processes, including the development and progression of cancer. Esophageal squamous cell carcinoma (ESCC) is a malignant cancer with high morbidity and recurrence in Asia. In the present study, the biological function of miR-125b and its underlying mechanism in ESCC were explored. The results revealed that miR-125b expression was significantly decreased in ESCC tissues and cell lines. A decrease in miR-125b was markedly related to lymphatic metastasis in patients. Functional analysis revealed that the overexpression of miR-125b using miR-125b mimics significantly inhibited cell growth and induced cell apoptosis, and increased the G1 phase of the cell cycle in EC109 and EC9706 cells. Notably, the miR-125b inhibitors revealed the opposite effect. Additionally, overexpression of miR-125b significantly inhibited tumor growth in vivo. Furthermore, BCL-2-modifying factor (BMF) was considered to be a potential candidate target of miR-125b based on miRNA target databases. miR-125b negatively regulated BMF expression by directly binding to its 3'-untranslated region. BMF was a functional target of miR-125b in the regulation of cell proliferation, cell apoptosis and the cell cycle in EC109 and EC9706 cells. In clinical ESCC specimens, BMF expression was upregulated, and negatively correlated with that of miR-125b. In conclusion, miR-125b had an antitumor role in ESCC cells mediated by targeting BMF, which can be potentially useful for tumorigenesis in ESCC.