CD150­dependent activation of EBV­transformed B cells induces the differentiation of peripheral blood monocytes via the secretion of multiple cytokines.

CD150, also termed signaling lymphocyte activation molecule family member 1, is a cell surface receptor expressed on T cells, B cells, dendritic cells (DCs) and some tumors. Stimulation of CD150 on immune cells induces cell proliferation and cytokine production. However, the function of CD150 in Epstein­Barr virus (EBV)­infected B cells is still not fully understood. In the present study, CD150 expression on B cells increased rapidly following EBV infection, and various CD150 antibodies, measles viral proteins and recombinant CD150 proteins induced the secretion of multiple cytokines in both CD150+ EBV­transformed B cells and EBV+ lymphoma cells. Notably, the IL­1α protein level showed the greatest increase among all cytokines measured. The culture supernatant containing these cytokines induced the rapid differentiation of monocytes to DCs after only 2 days in vitro, which was faster than the established DC maturation time. Furthermore, knockdown of CD150 expression led to a reduction in the secretion of multiple cytokines, and monocyte differentiation was partially inhibited by anti­IL­1α and anti­granulocyte­macrophage colony­stimulating factor neutralizing antibodies. Collectively, the results of the present study suggest that CD150 activation triggers cytokine production in EBV­transformed B cells, and that measles virus coinfection might affect immune responses through the production of various cytokines in EBV+ lymphoma cells.

Development of web-based software for environmental impact assessment focusing on road traffic noise.

In the Republic of Korea, Environmental Impact Assessment (EIAs) precedes development projects to predict and analyze potential environmental effects. Generally, EIA noise evaluations utilize 2D noise prediction equations and correction coefficients. This method, however, offers only a sectional noise evaluation and has limitations in complex environments with diverse noise sources. Moreover, the determination of various variables during the EIA process based on subjective human judgment raises concerns about the reliability of the results. Thus, this study aims to develop software accessible via a web environment for user-friendly EIA noise evaluations. This software supports integrated data management and generates a 3D noise prediction model for more precise and realistic analysis of noise impacts, specifically focusing on road-traffic noise at this stage of development. The 3D noise prediction model and noise map generated by the developed software have been validated against through comparison with the results of onsite noise measurements and commercial EIA software, SoundPLAN. This validation aimed to assess the practical utility of the application.

Non-Fullerene Acceptors with Benzodithiophene-Based Fused Planar Ring Cores for Organic Solar Cells.

Fused aromatic rings are widely employed in organic solar cell (OSC) materials due to their planarity and rigidity. Here, we designed and synthesized four two-dimensional non-fullerene acceptors, D6-4F, D6-4Cl, DTT-4F, and DTT-4Cl, based on two new fused planar ring structures of f-DTBDT-C6 and f-DTTBDT. Owing to the desirable phase separation formed in the blend films and the higher energy levels induced by the extra alkyl groups, PM6:D6-4F-based devices achieved a high VOC = 0.91 V with PCE = 11.10%, FF = 68.54%, and JSC = 17.75 mA/cm2. Because of the longer π-conjugation of the f-DTTBDT core with nine fused rings, DTT-4F and DTT-4Cl showed high molar extinction coefficients and broad absorption bands that enhanced the current density of OSCs. Finally, the PM6:DTT-4F-based devices achieved a JSC = 19.82 mA/cm2 with PCE = 9.68%, VOC = 0.83 V, and FF = 58.85%.

The therapeutic effects on U87 and SAS cells using Proton Linac based Boron Neutron Capture Therapy in Korea.

A proton linac based boron neutron capture therapy system (A-BNCT, 10MeV, 4mA) was successfully developed in Korea. We performed in vitro experiments with U87 and SAS cells and revealed the efficacy of a binary therapy BNCT using epithermal neutrons and boronophenylalanine (BPA). The results revealed that BNCT showed cancer cell selectivity and caused cell death. Further in vitro studies can be a valuable method to characterize an A-BNCT system. We expect BNCT to become a treatment option for cancer patients.

Effects of spectral variability due to sediment and bottom characteristics on remote sensing for suspended sediment in shallow rivers.

Advances in remote sensing techniques for water environments have led to acquisition of abundant data on suspended sediment concentration (SSC). However, confounding factors, such as particle sizes, mineral properties, and bottom materials, have not been fully studied, despite their substantial interference with the detection of intrinsic signals of suspended sediments. Therefore, we investigated the spectral variability arising from the sediment and bottom using laboratory and field-scale experiments. In the laboratory experiment, we focused on measuring spectral characteristics of suspended sediment according to particle size and sediment type. The laboratory experiment was conducted under conditions of completely mixed sediment and non-bottom reflectance using a specially designed rotating horizontal cylinder. To investigate the effects of different channel bottoms under sediment-laden flow conditions, we performed sediment tracer tests in field-scale channels comprising sand and vegetated bottoms. Based on experimental datasets, we performed spectral analysis and multiple endmember spectral mixture analysis (MESMA) to quantify the effect of spectral variability of sediment and bottom on the relationship between hyperspectral data and SSC. The results showed that optimal spectral bands were precisely estimated under non-bottom reflectance conditions, and the effective wavelengths depended on the sediment type. The fine sediments had a higher backscattering intensity compared to the coarse sediments, and the reflectance difference according to the particle size difference increased as the SSC increased. However, in the field-scale experiment, the bottom reflectance substantially decreased the R2 in the relationship between the hyperspectral data and SSC. Nevertheless, MESMA can quantify the contribution of suspended sediment and bottom signals as fractional images. Moreover, the suspended sediment fraction had a clear exponential relationship with SSC in all cases. We conclude that MESMA-driven sediment fractions could be an important alternative for estimating SSC in shallow rivers, as it quantifies the contributions of each factor and then minimizes the bottom effect.

Minimally Invasive Derotational Osteotomy of Long Bones: Smartphone Application Used to Improve the Accuracy of Correction.

Correction of rotational malalignments caused by fractures is essential as it may cause pain and gait disturbances. This study evaluated the intraoperative use of a smartphone application (SP app) to measure the extent of corrective rotation in patients treated using minimally invasive derotational osteotomy. Intraoperatively, two parallel 5 mm Schanz pins were placed above and below the fractured/injured site, and derotation was performed manually after percutaneous osteotomy. A protractor SP app was used intraoperatively to measure the angle between the two Schanz pins (angle-SP). Intramedullary nailing or minimally invasive plate osteosynthesis was performed after derotation, and computerized tomography (CT) scans were used to assess the angle of correction postoperatively (angle-CT). The accuracy of rotational correction was assessed by comparing angle-SP and angle-CT. The mean preoperative rotational difference observed was 22.1°, while the mean angle-SP and angle-CT were 21.6° and 21.3°, respectively. A significant positive correlation between angle-SP and angle-CT was observed, and 18 out of 19 patients exhibited complete healing within 17.7 weeks (1 patient exhibited nonunion). These findings suggest that using an SP app during minimally invasive derotational osteotomy can result in accurate correction of malrotation of long bones in a reproducible manner. Therefore, SP technology with integrated gyroscope function represents a suitable alternative for determination of the magnitude of rotational correction when performing corrective osteotomy.

The Anti-Tumor Effect of Boron Neutron Capture Therapy in Glioblastoma Subcutaneous Xenograft Model Using the Proton Linear Accelerator-Based BNCT System in Korea.

Boron neutron capture therapy (BNCT) is a radiation therapy that selectively kills cancer cells and is being actively researched and developed around the world. In Korea, development of the proton linear accelerator-based BNCT system has completed development, and its anti-cancer effect in the U-87 MG subcutaneous xenograft model has been evaluated. To evaluate the efficacy of BNCT, we measured 10B-enriched boronophenylalanine (BPA) uptake in U-87 MG, FaDu, and SAS cells and evaluated cell viability by clonogenic assays. In addition, the boron concentration in the tumor, blood, and skin on the U-87 MG xenograft model was measured, and the tumor volume was measured for 4 weeks after BNCT. In vitro, the intracellular boron concentration was highest in the order of SAS, FaDu, and U-87 MG, and cell survival fractions decreased depending on the BPA treatment concentration and neutron irradiation dose. In vivo, the tumor volume was significantly decreased in the BNCT group compared to the control group. This study confirmed the anti-cancer effect of BNCT in the U-87 MG subcutaneous xenograft model. It is expected that the proton linear accelerator-based BNCT system developed in Korea will be a new option for radiation therapy for cancer treatment.

Surrogate prediction of the breakthrough curve of solute transport in rivers using its reach length dependence.

Techniques for predicting the contaminant cloud propagation along a stream are necessary for swift action against contaminant spill accidents in fluvial systems. Due to their low computational cost, one-dimensional solute transport models have conventionally been employed, in which the complex channel characteristics are considered using model parameters. However, the determination of such parameters relies predominantly on optimization techniques based on pre-measured tracer data, which are usually unavailable for unexpected accidents. The present paper suggests an alternative method for predicting a breakthrough curve (BTC) variation along an unmeasured stream reach where no flow information is provided. In this study, we investigated the relationship between directly-measured flow properties and BTC characteristics based on field tracer experiments. Using statistical features of the tracer BTCs, we devised a regressive prediction method for estimating the BTC features as a function of travel distance, and validated the method by comparison with simulations using both a one-dimensional advection-dispersion equation (ADE) and transient storage model (TSM), whose parameters were calibrated at upstream reaches. The proposed regressive predictions were relatively accurate than those from parameter-calibrated models, and this advantage was more apparent for long-distance predictions for the unmeasured river reach.

Hyperspectral retrievals of suspended sediment using cluster-based machine learning regression in shallow waters.

Remote sensing of suspended sediment in shallow waters is challenging because of the increased optical variability of the water, resulting from the influence of suspended matter in the water column and the heterogeneous bottom properties. To overcome this limitation, in this study, we developed a novel framework called cluster-based machine learning regression for optical variability (CMR-OV), using the Gaussian mixture model (GMM) clustering technique and a random forest regressor (RFR). We evaluated the model using an optically complex dataset from a field-scale experiment. This experiment was conducted with four sediment types injected into an experimental meandering channel divided into two reaches with submerged vegetation and a natural sand bottom. We obtained high-resolution hyperspectral images using unmanned aerial vehicles (UAVs) and measured the in situ suspended sediment concentration using laser diffraction sensors. Based on optical similarity, we used CMR-OV to divide the hyperspectral dataset into several clusters. Then, we built separate RFR models for each cluster using the corresponding spectral bands that were selected using recursive feature elimination (RFE). Thus, we found that the proposed CMR-OV yielded superior results compared to the conventional RFR model, decreasing the total error score by 10.81%. The optical spectral bands of each cluster were distinguished from each other, indicating that the datasets that were spectrally discriminated from clustering enhanced the performance of the estimator. By comparing the clustered spectral dataset and physical factors, we proved the bottom type was the most critical factor in separating the clusters, even though the variability in the sediment properties also induced substantial spectral changes. Our findings demonstrated that CMR-OV accurately reproduced the spatiotemporal distribution of suspended sediment under optically complex conditions by addressing the heterogeneity of bottom reflectance in shallow water.

Matched Comparison of Bone Transport Using External Fixator Over a Nail Versus External Fixator Over a Plate for Segmental Tibial Bone Defects.

OBJECTIVE: To compare the outcomes and complications of bone transport over a nail (BTON) with those of bone transport over a plate (BTOP) for segmental tibial bone defects. DESIGN: Retrospective matched study design. SETTING: A major metropolitan tertiary referral trauma center. PATIENTS: Thirty-six patients with segmental tibial bone defects of >4 cm were included in this study. INTERVENTION: Either BTON or BTOP was performed on 18 patients. MAIN OUTCOME MEASUREMENTS: We compared the healing of the distraction process and of the docking site between the techniques. Distraction parameters including external fixator (EF) time, external fixation index, and healing index were compared. Bone and functional results were compared according to the Paley-Maar classification. Complications associated with each procedure were compared. RESULTS: Both BTON and BTOP achieved similar rates of primary union (83% vs. 89%) at the distraction or docking site. Significantly less time wearing an EF was needed for BTOP than for BTON (2.8 vs. 5.4 months; P < 0.01). The external fixation index was significantly lower for BTOP than for BTON (0.45 vs. 0.94 mo/cm; P < 0.01), whereas the healing indexes were similar. The final outcomes and complication incidences were not significantly different. CONCLUSIONS: The EF time was significantly shorter for BTOP than for BTON; however, the final outcomes were similar. Therefore, BTOP could be considered an attractive option for bone transport in patients with segmental tibial defects. LEVEL OF EVIDENCE: Therapeutic Level III. See Instructions for Authors for a complete description of levels of evidence.

Identification Framework of Contaminant Spill in Rivers Using Machine Learning with Breakthrough Curve Analysis.

To minimize the damage from contaminant accidents in rivers, early identification of the contaminant source is crucial. Thus, in this study, a framework combining Machine Learning (ML) and the Transient Storage zone Model (TSM) was developed to predict the spill location and mass of a contaminant source. The TSM model was employed to simulate non-Fickian Breakthrough Curves (BTCs), which entails relevant information of the contaminant source. Then, the ML models were used to identify the BTC features, characterized by 21 variables, to predict the spill location and mass. The proposed framework was applied to the Gam Creek, South Korea, in which two tracer tests were conducted. In this study, six ML methods were applied for the prediction of spill location and mass, while the most relevant BTC features were selected by Recursive Feature Elimination Cross-Validation (RFECV). Model applications to field data showed that the ensemble Decision tree models, Random Forest (RF) and Xgboost (XGB), were the most efficient and feasible in predicting the contaminant source.

Automatic Multi-Stage Cold Forging of an SUS304 Ball-Stud with a Hexagonal Hole at One End.

SUS304 stainless steel is characterized by combined tensile and compression testing, with an emphasis on flow stress at higher strain and temperature. The plastic deformation behavior of SUS304 from room temperature to 400 °C is examined and a general approach is used to express flow stress as a closed-form function of strain, strain rate, and temperature; this is optimal when the strain is high, especially during automatic multi-stage cold forging. The fitted flow stress is subjected to elastothermoviscoplastic finite element analysis (FEA) of an automatic multi-stage cold forging process for an SUS304 ball-stud. The importance of the thermal effect during cold forging, in terms of high material strength and good strain-hardening, is revealed by comparing the forming load, die wear and die stress predictions of non-isothermal and isothermal FEAs. The experiments have shown that the predictions of isothermal FEA are not feasible because of the high predicted effective stress on the weakest part of the die.

Therapeutic effect of Shinkiwhan, herbal medicine, regulates OPG/RANKL/RANK system on ovariectomy-induced bone loss rat.

PURPOSE: Although physical activity is required to prevent or ameliorate osteoporosis, medicine prescription should precede it, since it may be limited in severe osteoporosis patients. Furthermore, osteoporosis has a great effect on physical activity disorders that accompany fractures and pain, and therefore, research on treatment or prevention to decrease the number of patients is required. The purpose of this study was to discover candidate substances from natural products with an effective pharmacological action and to prepare basic data to help patients. METHODS: To prepare the osteoporosis model, ovariectomy (OVX) was performed using surgical methods. The prepared prescription [Shinkiwhan (SKH), a Korean medicine] was administered orally at a dose of 210 mg/kg/day for 8 weeks. After completion of the animal experiment, the bone mineral density (BMD) was analyzed using double-energy X-ray absorptiometry. The analysis of the effect of drugs on bones was performed using histological analysis and immunostaining. RESULTS: SKH increased the BMD in the OVX rats. Furthermore, SKH significantly increased the expression of osteoprotegerin and downregulated receptor activator of nuclear factor kappa B ligand and phosphorylation of c-jun N-terminal kinases in the bones of the OVX model. CONCLUSION: Our findings suggest a protective effect of SKH against BMD loss in the OVX model.

Effect of chitinase-3-like protein 1 on glucose metabolism: In vitro skeletal muscle and human genetic association study.

We investigated the effect of chitinase-3-like protein 1 (CHI3L1) on glucose metabolism and its underlying mechanisms in skeletal muscle cells, and evaluated whether the observed effects are relevant in humans. CHI3L1 was associated with increased glucose uptake in skeletal muscles in an AMP-activated protein kinase (AMPK)-dependent manner, and with increased intracellular calcium levels via PAR2. The improvement in glucose metabolism observed in an intraperitoneal glucose tolerance test on male C57BL/6J mice supported this association. Inhibition of the CaMKK was associated with suppression of CHI3L1-mediated glucose uptake. Additionally, CHI3L1 was found to influence glucose uptake through the PI3K/AKT pathway. Results suggested that CHI3L1 stimulated the phosphorylation of AS160 and p38 MAPK downstream of AMPK and AKT, and the resultant GLUT4 translocation. In primary myoblast cells, stimulation of AMPK and AKT was observed in response to CHI3L1, underscoring the biological relevance of CHI3L1. CHI3L1 levels were elevated in cells under conditions that mimic exercise in vitro and in exercised mice in vivo, indicating that CHI3L1 is secreted during muscle contraction. Finally, similar associations between CHI3L1 and metabolic parameters were observed in humans alongside genotype associations between CHI3L1 and diabetes at the population level. CHI3L1 may be a potential therapeutic target for the treatment of diabetes.

Anticancer Activity of Liquid Treated with Microwave Plasma-Generated Gas through Macrophage Activation.

Reactive nitrogen species (RNS), including nitric oxide (NO·) has been known as one of the key regulatory molecules in the immune system. In this study, we generated RNS-containing water treated with microwave plasma-generated gas in which the major component was nitric oxide (PGNO), and the effect on the macrophage polarization was investigated. The RNS-containing water was diluted in complete cell culture media (PGNO-solution) into the concentration that did not induce cell death in RAW 264.7 murine macrophages. PGNO-solution upregulates M1-type macrophage activation and downregulates the characteristics of M2-type macrophage at the transcriptional level. In addition, the PGNO-solution-treated M2-like macrophages had higher potential in killing melanoma cells. The anticancer potential was also investigated in a syngeneic mouse model. Our results show that PGNO-solution has the potential to convert the fate of macrophages, suggesting PGNO-solution treatment as a supportive method for controlling the function of macrophages under the tumor microenvironment.

Comparison of Bone Healing in Open-Wedge High Tibial Osteotomy between the Use of Allograft Bone Chips with Autologous Bone Marrow and the Use of Allograft Bone Chips Alone for Gap Filling.

The present study aimed to evaluate whether the use of allograft bone chips mixed with autologous bone marrow (BM) in the high tibial osteotomy (HTO) gap could improve the radiological and clinical results of HTO. This study analyzed 36 patients who underwent HTO with locking plate (mean age: 58.0 years). Allograft bone chips mixed with autologous BM aspirated from anterior superior iliac spine were used in 19 patients (group A) and allograft chips only were used in 17 patients (group B). The radiological and clinical results between two groups were compared during examination at 6 weeks, 3 months, 6 months, and 12 months after surgery. Clinical evaluations involving the Hospital for Special Surgery score, Knee Society knee score, and function score were performed at each assessment point. The osteotomy filling and osteoconductivity using the modified van Hemert's score were compared in each period. The clinical results were not different between the groups at all assessment points. Osteotomy filling was higher at 6 weeks and 3 months in group A than in group B (p = 0.004 and 0.005, respectively). Osteoconductivity was higher at 6 weeks and 3 months in the most medial » zone in group A than in group B (p = 0.025 and 0.031, respectively). Our data shows it is beneficial to mix the allograft bone chips mixed with autologous BM after open-wedge HTO.

Metformin overcomes resistance to cisplatin in triple-negative breast cancer (TNBC) cells by targeting RAD51.

BACKGROUND: Chemotherapy is a standard therapeutic regimen to treat triple-negative breast cancer (TNBC); however, chemotherapy alone does not result in significant improvement and often leads to drug resistance in patients. In contrast, combination therapy has proven to be an effective strategy for TNBC treatment. Whether metformin enhances the anticancer effects of cisplatin and prevents cisplatin resistance in TNBC cells has not been reported. METHODS: Cell viability, wounding healing, and invasion assays were performed on Hs 578T and MDA-MB-231 human TNBC cell lines to demonstrate the anticancer effects of combined cisplatin and metformin treatment compared to treatment with cisplatin alone. Western blotting and immunofluorescence were used to determine the expression of RAD51 and gamma-H2AX. In an in vivo 4T1 murine breast cancer model, a synergistic anticancer effect of metformin and cisplatin was observed. RESULTS: Cisplatin combined with metformin decreased cell viability and metastatic effect more than cisplatin alone. Metformin suppressed cisplatin-mediated RAD51 upregulation by decreasing RAD51 protein stability and increasing its ubiquitination. In contrast, cisplatin increased RAD51 expression in an ERK-dependent manner. In addition, metformin also increased cisplatin-induced phosphorylation of γ-H2AX. Overexpression of RAD51 blocked the metformin-induced inhibition of cell migration and invasion, while RAD51 knockdown enhanced cisplatin activity. Moreover, the combination of metformin and cisplatin exhibited a synergistic anticancer effect in an orthotopic murine model of 4T1 breast cancer in vivo. CONCLUSIONS: Metformin enhances anticancer effect of cisplatin by downregulating RAD51 expression, which represents a novel therapeutic target in TNBC management.

Machine Learning Model to Predict Osteoporotic Spine with Hounsfield Units on Lumbar Computed Tomography.

OBJECTIVE: Bone mineral density (BMD) is an important consideration during fusion surgery. Although dual X-ray absorptiometry is considered as the gold standard for assessing BMD, quantitative computed tomography (QCT) provides more accurate data in spine osteoporosis. However, QCT has the disadvantage of additional radiation hazard and cost. The present study was to demonstrate the utility of artificial intelligence and machine learning algorithm for assessing osteoporosis using Hounsfield units (HU) of preoperative lumbar CT coupling with data of QCT. METHODS: We reviewed 70 patients undergoing both QCT and conventional lumbar CT for spine surgery. The T-scores of 198 lumbar vertebra was assessed in QCT and the HU of vertebral body at the same level were measured in conventional CT by the picture archiving and communication system (PACS) system. A multiple regression algorithm was applied to predict the T-score using three independent variables (age, sex, and HU of vertebral body on conventional CT) coupling with T-score of QCT. Next, a logistic regression algorithm was applied to predict osteoporotic or non-osteoporotic vertebra. The Tensor flow and Python were used as the machine learning tools. The Tensor flow user interface developed in our institute was used for easy code generation. RESULTS: The predictive model with multiple regression algorithm estimated similar T-scores with data of QCT. HU demonstrates the similar results as QCT without the discordance in only one non-osteoporotic vertebra that indicated osteoporosis. From the training set, the predictive model classified the lumbar vertebra into two groups (osteoporotic vs. non-osteoporotic spine) with 88.0% accuracy. In a test set of 40 vertebrae, classification accuracy was 92.5% when the learning rate was 0.0001 (precision, 0.939; recall, 0.969; F1 score, 0.954; area under the curve, 0.900). CONCLUSION: This study is a simple machine learning model applicable in the spine research field. The machine learning model can predict the T-score and osteoporotic vertebrae solely by measuring the HU of conventional CT, and this would help spine surgeons not to under-estimate the osteoporotic spine preoperatively. If applied to a bigger data set, we believe the predictive accuracy of our model will further increase. We propose that machine learning is an important modality of the medical research field.

Seasonally varying effects of environmental factors on phytoplankton abundance in the regulated rivers.

This study investigates a seasonally varying response of phytoplankton biomass to environmental factors in rivers. Artificial neural network (ANN) models incorporated with a clustering technique, the clustered ANN models, were employed to analyze the relationship between chlorophyll a (Chl-a) and the explanatory variables in the regulated Nakdong River, South Korea. The results show that weir discharge (Q) and total phosphorus (TP) were the most influential factors on temporal dynamics of Chl-a. The relative importance of both variables increased up to higher than 30% for low water temperature seasons with dominance of diatoms. While, during summer when cyanobacteria predominated, the significance of Q increased up to 45%, while that of TP declined to about 10%. These tendencies highlight that the effects of the river environmental factors on phytoplankton abundance was temporally inhomogeneous. In harmful algal bloom mitigation scenarios, the clustered ANN models reveals that the optimal weir discharge was 400 m3/s which was 67% of the value derived from the non-clustered ANN models. At the immediate downstream of confluence of the Kumho River, the optimal weir discharge should increase up to about 1.5 times because of the increase in the tributary pollutant loads attributed to electrical conductivity (EC).

LIF, a Novel Myokine, Protects Against Amyloid-Beta-Induced Neurotoxicity via Akt-Mediated Autophagy Signaling in Hippocampal Cells.

BACKGROUND: Leukemia inhibitory factor, a novel myokine, is known to be associated with neural function, but the underlying molecular mechanism remains unclear. METHODS: HT-22 mouse hippocampal cells, primary hippocampal cells, and Drosophila Alzheimer's disease model were used to determine the effect of leukemia inhibitory factor on neurons. Immunoblot analysis and immunofluorescence method were used to analyze biological mechanism. RESULTS: Leukemia inhibitory factor increased Akt phosphorylation in a phosphoinositide-3-kinase-dependent manner in hippocampal cells. Leukemia inhibitory factor also increased the phosphorylation of the mammalian target of rapamycin and the downstream S6K. Leukemia inhibitory factor stimulated the phosphorylation of signal transducer and activator of transcription via extracellular signal-regulated kinases. Leukemia inhibitory factor increased c-fos expression through both Akt and extracellular signal-regulated kinases. Leukemia inhibitory factor blocked amyloid ß-induced neural viability suppression and inhibited amyloid ß-induced glucose uptake impairment through the block of amyloid ß-mediated insulin receptor downregulation. Leukemia inhibitory factor blocked amyloid ß-mediated induction of the autophagy marker, microtubule-associated protein 1A/1B-light chain 3. Additionally, in primary prepared hippocampal cells, leukemia inhibitory factor stimulated Akt and extracellular signal-regulated kinase, demonstrating that leukemia inhibitory factor has physiological relevance in vivo. Suppression of the autophagy marker, light chain 3II, by leukemia inhibitory factor was observed in a Drosophila model of Alzheimer's disease. CONCLUSIONS: These results demonstrate that leukemia inhibitory factor protects against amyloid ß-induced neurotoxicity via Akt/extracellular signal-regulated kinase-mediated c-fos induction, and thus suggest that leukemia inhibitory factor is a potential drug for Alzheimer's disease.