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Long-term subcellular intravital imaging in mammals is vital to study diverse intercellular behaviors and organelle functions during native physiological processes. However, optical heterogeneity, tissue opacity, and phototoxicity pose great challenges. Here, we propose a computational imaging framework, termed digital adaptive optics scanning light-field mutual iterative tomography (DAOSLIMIT), featuring high-speed, high-resolution 3D imaging, tiled wavefront correction, and low phototoxicity with a compact system. By tomographic imaging of the entire volume simultaneously, we obtained volumetric imaging across 225 × 225 × 16 µm3, with a resolution of up to 220 nm laterally and 400 nm axially, at the millisecond scale, over hundreds of thousands of time points. To establish the capabilities, we investigated large-scale cell migration and neural activities in different species and observed various subcellular dynamics in mammals during neutrophil migration and tumor cell circulation.
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Algoritmos , Imageamento Tridimensional , Óptica e Fotônica , Tomografia , Animais , Cálcio/metabolismo , Linhagem Celular Tumoral , Membrana Celular/metabolismo , Movimento Celular , Drosophila , Células HeLa , Humanos , Larva/fisiologia , Fígado/diagnóstico por imagem , Masculino , Camundongos Endogâmicos C57BL , Neoplasias/patologia , Ratos Sprague-Dawley , Razão Sinal-Ruído , Frações Subcelulares/fisiologia , Fatores de Tempo , Peixe-ZebraRESUMO
Optical computing promises to improve the speed and energy efficiency of machine learning applications1-6. However, current approaches to efficiently train these models are limited by in silico emulation on digital computers. Here we develop a method called fully forward mode (FFM) learning, which implements the compute-intensive training process on the physical system. The majority of the machine learning operations are thus efficiently conducted in parallel on site, alleviating numerical modelling constraints. In free-space and integrated photonics, we experimentally demonstrate optical systems with state-of-the-art performances for a given network size. FFM learning shows training the deepest optical neural networks with millions of parameters achieves accuracy equivalent to the ideal model. It supports all-optical focusing through scattering media with a resolution of the diffraction limit; it can also image in parallel the objects hidden outside the direct line of sight at over a kilohertz frame rate and can conduct all-optical processing with light intensity as weak as subphoton per pixel (5.40 × 1018- operations-per-second-per-watt energy efficiency) at room temperature. Furthermore, we prove that FFM learning can automatically search non-Hermitian exceptional points without an analytical model. FFM learning not only facilitates orders-of-magnitude-faster learning processes, but can also advance applied and theoretical fields such as deep neural networks, ultrasensitive perception and topological photonics.
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Photonic computing enables faster and more energy-efficient processing of vision data1-5. However, experimental superiority of deployable systems remains a challenge because of complicated optical nonlinearities, considerable power consumption of analog-to-digital converters (ADCs) for downstream digital processing and vulnerability to noises and system errors1,6-8. Here we propose an all-analog chip combining electronic and light computing (ACCEL). It has a systemic energy efficiency of 74.8 peta-operations per second per watt and a computing speed of 4.6 peta-operations per second (more than 99% implemented by optics), corresponding to more than three and one order of magnitude higher than state-of-the-art computing processors, respectively. After applying diffractive optical computing as an optical encoder for feature extraction, the light-induced photocurrents are directly used for further calculation in an integrated analog computing chip without the requirement of analog-to-digital converters, leading to a low computing latency of 72 ns for each frame. With joint optimizations of optoelectronic computing and adaptive training, ACCEL achieves competitive classification accuracies of 85.5%, 82.0% and 92.6%, respectively, for Fashion-MNIST, 3-class ImageNet classification and time-lapse video recognition task experimentally, while showing superior system robustness in low-light conditions (0.14 fJ µm-2 each frame). ACCEL can be used across a broad range of applications such as wearable devices, autonomous driving and industrial inspections.
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Planar digital image sensors facilitate broad applications in a wide range of areas1-5, and the number of pixels has scaled up rapidly in recent years2,6. However, the practical performance of imaging systems is fundamentally limited by spatially nonuniform optical aberrations originating from imperfect lenses or environmental disturbances7,8. Here we propose an integrated scanning light-field imaging sensor, termed a meta-imaging sensor, to achieve high-speed aberration-corrected three-dimensional photography for universal applications without additional hardware modifications. Instead of directly detecting a two-dimensional intensity projection, the meta-imaging sensor captures extra-fine four-dimensional light-field distributions through a vibrating coded microlens array, enabling flexible and precise synthesis of complex-field-modulated images in post-processing. Using the sensor, we achieve high-performance photography up to a gigapixel with a single spherical lens without a data prior, leading to orders-of-magnitude reductions in system capacity and costs for optical imaging. Even in the presence of dynamic atmosphere turbulence, the meta-imaging sensor enables multisite aberration correction across 1,000 arcseconds on an 80-centimetre ground-based telescope without reducing the acquisition speed, paving the way for high-resolution synoptic sky surveys. Moreover, high-density accurate depth maps can be retrieved simultaneously, facilitating diverse applications from autonomous driving to industrial inspections.
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Widefield microscopy can provide optical access to multi-millimeter fields of view and thousands of neurons in mammalian brains at video rate. However, tissue scattering and background contamination results in signal deterioration, making the extraction of neuronal activity challenging, laborious and time consuming. Here we present our deep-learning-based widefield neuron finder (DeepWonder), which is trained by simulated functional recordings and effectively works on experimental data to achieve high-fidelity neuronal extraction. Equipped with systematic background contribution priors, DeepWonder conducts neuronal inference with an order-of-magnitude-faster speed and improved accuracy compared with alternative approaches. DeepWonder removes background contaminations and is computationally efficient. Specifically, DeepWonder accomplishes 50-fold signal-to-background ratio enhancement when processing terabytes-scale cortex-wide functional recordings, with over 14,000 neurons extracted in 17 h.
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Encéfalo , Cálcio , Animais , Encéfalo/fisiologia , Microscopia , Córtex Cerebral , Neurônios/fisiologia , MamíferosRESUMO
Krüppel-associated box zinc finger proteins (KZFPs) function as a defense mechanism to maintain the genome stability of higher vertebrates by regulating the transcriptional activities of transposable elements (TEs). While previous studies have characterized ZFP809 as responsible for binding and repressing ERVs containing a proline tRNA primer-binding site (PBS-Pro) in mice, comparable KZFPs have not been identified in humans yet. Here, we identified ZNF506 as a PBS-Pro-binding protein in humans, which functions as a transcriptional repressor of PBS-Pro-utilizing retroviruses by recruiting heterochromatic modifications. Although they have similar functions, the low protein similarities between ZNF506, ZFP809 and KZFPs of other species suggest their independent evolution against the invasion of PBS-Pro-utilizing retroviruses into their respective ancestor genomes after species divergence. We also explored the link between ZNF506 and leukemia. Our findings suggest that ZNF506 is a unique human KZFP that can bind to PBS-Pro, highlighting the diverse evolution of KZFPs in defending against retroviral invasions. Additionally, our study provides insights into the potential role of ZNF506 in leukemia, contributing to the expanding knowledge of KZFPs' crucial function in disease and genome stability.
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Retrovirus Endógenos , Leucemia , Animais , Humanos , Camundongos , Sítios de Ligação , Retrovirus Endógenos/genética , Retrovirus Endógenos/metabolismo , Instabilidade Genômica , Leucemia/genética , Proteínas Repressoras/metabolismoRESUMO
SignificanceHosts often target the relatively conserved regions in rapidly mutating retroviruses to inhibit their replication. One of these regions is called a primer binding site (PBS), which has to be complementary to the host tRNA to initiate reverse transcription. By analyzing endogenous retroviral elements, we found that host cells use this sequence as a target in efforts to block the expression of viral elements. A specific type of zinc finger protein targets the PBS in a host genome, which not only inhibits the transcription of endogenous viruses but also inhibits the replication of exogenous retroviruses with the same PBS. Thus, our study sheds light on a strategy for searching for host restriction factors targeting retroviruses.
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Regulação Viral da Expressão Gênica , Interações Hospedeiro-Patógeno , RNA Viral/genética , RNA Viral/metabolismo , Proteínas Repressoras/metabolismo , Retroviridae/fisiologia , Dedos de Zinco , Sequência de Bases , Sítios de Ligação , Mapeamento Cromossômico , Retrovirus Endógenos , Estudo de Associação Genômica Ampla , Humanos , Motivos de Nucleotídeos , Retroviridae/classificação , Transcrição Gênica , Replicação ViralRESUMO
Calcium imaging has transformed neuroscience research by providing a methodology for monitoring the activity of neural circuits with single-cell resolution. However, calcium imaging is inherently susceptible to detection noise, especially when imaging with high frame rate or under low excitation dosage. Here we developed DeepCAD, a self-supervised deep-learning method for spatiotemporal enhancement of calcium imaging data that does not require any high signal-to-noise ratio (SNR) observations. DeepCAD suppresses detection noise and improves the SNR more than tenfold, which reinforces the accuracy of neuron extraction and spike inference and facilitates the functional analysis of neural circuits.
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Potenciais de Ação , Algoritmos , Cálcio/metabolismo , Diagnóstico por Imagem/métodos , Processamento de Imagem Assistida por Computador/métodos , Neurônios/fisiologia , Razão Sinal-Ruído , Animais , Feminino , Masculino , Camundongos , Camundongos Transgênicos , Neurônios/citologiaRESUMO
DNA methylation aberrations have a strong correlation with cancer in early detection, diagnosis, and prognosis, which make them possible candidate biomarkers. Electrochemical biosensors offer rapid protocols for detecting DNA methylation status with minimal pretreatment of samples. However, the inevitable presence of background current in the time domain, including electrochemical noise and variations, limits the detection performance of these biosensors, especially for low concentration analytes. Here, we propose an ultrasensitive frequency-domain electrochemical analysis strategy to effectively separate the weak signals from background current. To achieve this, we employed periodic magnetic field modulation of magnetic beads (MBs) on and off the electrode surface to generate a periodic electrochemical signal for subsequent frequency-domain analysis. By capturing labeled MBs with as low as 0.5 pg of DNA, we successfully demonstrated a highly sensitive electrochemical method for determination of genome-wide DNA methylation levels. We also validated the effectiveness of this methodology using DNA samples extracted from three types of hepatocellular carcinoma (HCC) cell lines. The results revealed varying genomic methylation levels among different HCC cell lines, indicating the potential application of this approach for early-stage cancer detection in terms of DNA methylation status.
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BACKGROUND: Laparoscopic duodenum-preserving pancreatic head resection (LDPPHR) is a surgical method used to treat benign and low-grade malignant pancreatic head tumors. This study aimed to determine the protective effect of common bile duct in LDPPHR using indocyanine green (ICG) fluorescence imaging. METHODS: A retrospective analysis of 30 patients treated with LDPPHR at the Second Affiliated Hospital of Nanchang University between January 2015 and November 2022 was performed. Patients were divided into two groups based on ICG use: ICG and non-ICG. RESULTS: Thirty patients received LDPPHR, 11 males and 19 females, and the age was 50.50 (M (IQR)) years (range: 19-76 years). LDPPHR was successfully performed in 27 (90 %) patients, LPD was performed in 1 (3 %) patient, and laparotomy conversion was performed in 2 (7 %) patients. One patient (3 %) died 21 days after surgery. The incidence of intraoperative bile duct injury in the ICG group was lower than that in the non-ICG group (10 % vs 60 %, P = 0.009), and the operation time in the ICG group was shorter than that in the non-ICG group (311.9 ± 14.97 vs 338.05 ± 18.75 min, P < 0.05). Postoperative pancreatic fistula occurred in 16 patients (53 %), including 10 with biochemical leakage (62.5 %), four with grade B (25 %), and two with grade C (12.5 %). Postoperative bile leakage occurred in four patients (13 %). CONCLUSIONS: The ICG fluorescence imaging technology in LDPPHR helps protect the integrity of the common bile duct and reduce the occurrence of intraoperative bile duct injury, postoperative bile leakage, and bile duct stenosis.
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Doenças dos Ductos Biliares , Laparoscopia , Masculino , Feminino , Humanos , Verde de Indocianina , Estudos Retrospectivos , Laparoscopia/métodos , Doenças dos Ductos Biliares/etiologia , Imagem Óptica/efeitos adversos , Imagem Óptica/métodos , Duodeno/diagnóstico por imagem , Duodeno/cirurgiaRESUMO
BACKGROUND: Long coronavirus disease (COVID) after COVID-19 infection is continuously threatening the health of people all over the world. Early prediction of the risk of Long COVID in hospitalized patients will help clinical management of COVID-19, but there is still no reliable and effective prediction model. METHODS: A total of 1905 hospitalized patients with COVID-19 infection were included in this study, and their Long COVID status was followed up 4-8 weeks after discharge. Univariable and multivariable logistic regression analysis were used to determine the risk factors for Long COVID. Patients were randomly divided into a training cohort (70%) and a validation cohort (30%), and factors for constructing the model were screened using Lasso regression in the training cohort. Visualize the Long COVID risk prediction model using nomogram. Evaluate the performance of the model in the training and validation cohort using the area under the curve (AUC), calibration curve, and decision curve analysis (DCA). RESULTS: A total of 657 patients (34.5%) reported that they had symptoms of long COVID. The most common symptoms were fatigue or muscle weakness (16.8%), followed by sleep difficulties (11.1%) and cough (9.5%). The risk prediction nomogram of age, diabetes, chronic kidney disease, vaccination status, procalcitonin, leukocytes, lymphocytes, interleukin-6 and D-dimer were included for early identification of high-risk patients with Long COVID. AUCs of the model in the training cohort and validation cohort are 0.762 and 0.713, respectively, demonstrating relatively high discrimination of the model. The calibration curve further substantiated the proximity of the nomogram's predicted outcomes to the ideal curve, the consistency between the predicted outcomes and the actual outcomes, and the potential benefits for all patients as indicated by DCA. This observation was further validated in the validation cohort. CONCLUSIONS: We established a nomogram model to predict the long COVID risk of hospitalized patients with COVID-19, and proved its relatively good predictive performance. This model is helpful for the clinical management of long COVID.
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COVID-19 , Nomogramas , SARS-CoV-2 , Humanos , COVID-19/epidemiologia , COVID-19/complicações , COVID-19/diagnóstico , Masculino , Feminino , Pessoa de Meia-Idade , Prognóstico , Fatores de Risco , Estudos de Coortes , Idoso , Adulto , Hospitalização/estatística & dados numéricos , Medição de Risco , Síndrome de COVID-19 Pós-AgudaRESUMO
Twenty-nine sesquiterpenoids, including pseudoguaiane-type (1-11), eudesmane-type (12-23), and carabrane-type (24-29), have been identified from the plant Carpesium abrotanoides. Of them, compounds 1-4, 12-15, and 24-27, namely carpabrotins A-L, are twelve previously undescribed ones. Compound 3 possessed a pseudoguaiane backbone with a rearrangement modification at C-11, C-12 and C-13, while compound 4 suffered a carbon bond break between the C-4 and C-5 to form a rare 4,5-seco-pseudoguaiane lactone. Compounds 1-3, 5, 13-16 and 25-27 exhibited anti-inflammatory activity by inhibiting NO production in LPS-induced RAW264.7 macrophages with IC50 values less than 40 µM, while compounds 1, 2, 5, 13, 14, 16, and 25-27 showed significant inhibitory activity comparable to that of dexamethasone. The anti-atopic dermatitis (AD) effects of compounds 5 and 16 were tested according to 2,4-dinitrochlorobenzene (DNCB)-induced AD-like skin lesions in KM mice, and the results revealed that the major products 5 and 16 improved the histological features of AD-like skin lesions and mast cell infiltration in mice. This study suggested that sesquiterpenoids in C. abrotanoides should play a key role in its anti-inflammatory use.
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Phenanthrene (Phe) is a commonly occurring polycyclic aromatic hydrocarbon (PAH) found in various food sources and drinking water. Previous studies have shown that long-term exposure to Phe in male mice leads to insulin resistance in a dose-dependent manner. However, the effect of Phe on glucose homeostasis in female mice remains unknown. To address this knowledge gap, female Kunming mice were exposed to Phe through their drinking water at concentrations of 0.05, 0.5, and 5 ng/mL. After 270 d of exposure, we surprisingly discovered a low-dose effect of Phe on insulin resistance in female mice, which differed from the effect observed in male mice and showed sexual dimorphism. Specifically, insulin resistance was only observed in the 0.05 ng/mL treatment, and this low-dose effect was also reflected in the concentration of Phe in white adipose tissue (WAT). Differences in metabolic enzyme activities in the liver may potentially explain this effect. The observed sexual dimorphism in Phe exposure could be attributed to variations in estrogen (E2) level and estrogen receptor beta (ERß) expression in WAT. These findings highlight the association between environmental factors and the development of insulin resistance, emphasizing the pathogenic effect of even low doses of Phe. Moreover, sex dependent-effect should be given more attention when studying the toxic effects of environmental pollutants.
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Objective: The objective of this study was to integrate metabolomics and transcriptomics data to identify key diagnostic and prognostic markers for esophageal squamous cell carcinoma (ESCC). Plasma samples were collected from 85 ESCC patients at different stages and 50 healthy volunteers for non-targeted metabolomic analysis. Methods: Liquid chromatography-tandem mass spectrometry (LC-MS/MS) was employed for non-targeted metabolomic analysis. Subsequently, we integrated the metabolomic data with transcriptomic data from the Gene Expression Omnibus (GEO) and prognosis data from The Cancer Genome Atlas Program (TCGA) to perform pathway analysis. Our focus was on pathways that involve both metabolites and upstream genes, as they often exhibit higher accuracy. Results: Through the integration of metabolomics and transcriptomics, we identified significant alterations in the platelet activation pathway in ESCC. This pathway involves the participation of both metabolites and genes, making it a more accurate reflection of pathological changes associated with the disease. Notably, metabolite arachidonic acid (AA) and chemokine receptor type 2(CXCR2) were significantly downregulated in ESCC, while genes collagen type I alpha 1(COL1A1), collagen type I alpha 2(COL1A2), collagen type III alpha 1(COL3A1), type 3 inositol 1,4,5-trisphosphate receptor (ITPR3), and insulin-like growth factor II mRNA binding protein 3(IGF2BP3) were significantly upregulated, indicating the presence of tumor-induced platelet activation in ESCC. Further analysis of prognosis data revealed that high expression of COL1A1, IGF2BP3, and ITPR3 was associated with a favorable prognosis for ESCC, while high CXCR2 expression was linked to an adverse prognosis. In addition, we combined COL1A1, ITPR3, IGF2BP3, CXCR2, and AA to form a diagnostic biomarker panel. The receiver operating characteristic curve (ROC) demonstrated excellent diagnostic capability (AUC=0.987). Conclusion: Our study underscores the significant role of platelet activation pathways and related genes in the diagnosis and prognosis of ESCC patients. These findings offer promising insights for improving the clinical management of ESCC.
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Zinc dialkyldithiophosphate (ZDDP), the most widely used antiwear additive in engine oils, has been extensively studied over the last few decades to help understand the origin of its effectiveness. Glassy phosphate-based tribofilms, approximately 100 nm thick, are often formed on surfaces sliding in ZDDP-containing oils, which help to prevent or reduce wear. Recent studies reveal that a combination of applied shear and compressive stresses drive mechanochemical reactions that promote tribofilm growth, and that growth is further accelerated by increased temperature. While recent work has shown that compressive stress alone is insufficient to form tribofilms, the individual effects of the shear stress and compressive stress are not fully understood. Here, shear and compressive stresses are studied separately by using different ratios of high-viscosity, high-traction fluids for testing. This allows the areal mean compressive and shear stresses in the fluid when confined at a loaded sliding interface, to be independently controlled while driving tribofilm growth, which is a system we refer to as a stress-controlled mechanochemical reactor. Tribofilms derived from a secondary ZDDP were generated using a tungsten carbide/tungsten carbide ball-on-disk contact in the full elastohydrodynamic lubrication (EHL) regime using a mini-traction machine (MTM), meaning that solid-solid contact is avoided. The MTM was equipped with a spacer layer imaging (SLIM) capability, permitting in situ measurement of the tribofilm thickness during its growth. The well-separated sliding surfaces generated by the high-viscosity fluids confirm that solid-solid contact is not required for tribofilm formation. Under these full fluid film EHL conditions, shear stress and temperature promote tribofilm growth in accordance with stress-augmented thermal activation. In contrast, under constant shear stress and temperature, compressive stress has the opposite effect, inhibiting tribofilm growth. Using the extended Eyring model for shear- and hydrostatic pressure-affected reaction kinetics, an activation energy of 0.54 ± 0.04 eV is found, consistent with prior studies of ZDDPs. The activation volume for shear stress is found to be 0.18 ± 0.06 nm3, while that for the compressive stress component is much smaller, at 0.010 ± 0.004 nm3. This not only confirms prior work supporting that shear stress drives tribofilm growth, but demonstrates and quantifies how compressive stress inhibits growth, consistent with the rate-limiting step in tribofilm growth involving a bond-breaking reaction. Implications of these findings are discussed.
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Sweat, as a sample that includes a lot of biochemical information, is good for non-invasive monitoring. In recent years, there have been an increasing number of studies on in situ monitoring of sweat. However, there are still some challenges for the continuous analysis of samples. As a hydrophilic, easy-to-process, environmentally friendly, inexpensive and easily accessible material, paper is an ideal substrate material for making in situ sweat analysis microfluidics. This review introduces the development of paper as a sweat analysis microfluidic substrate material, focusing on the advantages of the structural characteristics of paper, trench design and equipment integration applications to expand the design and research ideas for the development of in situ sweat detection technology.
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Técnicas Biossensoriais , Dispositivos Eletrônicos Vestíveis , Microfluídica , Suor/químicaRESUMO
Chlorpromazine (CPZ) is a medicine for nervous system disorders. Measuring CPZ in vivo can assist doctors in evaluating patients' blood drug concentration and monitoring drug metabolism. Therefore, an accurate in vivo detection of CPZ is crucial. In recent years, the acupuncture needle, traditionally used in Chinese medicine, has emerged as a potential electrode in the field of electrochemistry, with promising applications for in vivo detection. In this study, Au/Cu nanoparticles were electrodeposited onto an acupuncture needle electrode (ANE) to improve electrical conductivity and provide an electro-catalytic surface. Subsequently, 3-aminophenylboronic acid and CPZ were attracted to each other through intermolecular forces; at the same time, the interaction force of Au-S between CPZ and the AuNPs made the polymer layer grow around the CPZ molecules on the modified electrode surface. The imprinted nanocavities showed highly selective and sensitive detection performance for CPZ after elution. Inside the recognizable site and microenvironment of the cavities, the captured CPZ molecule provided a suitable configuration for the fluent electron transfer of the electroactive group within a short range from the Au/Cu bimetal. Under ideal conditions, the MIP/Au/Cu/ANE exhibited two good linear ranges of 0.1-100 µM and 100-1000 µM with a detection limit of 0.07 µM. Moreover, the sensors showed great selectivity, good stability and excellent repeatability, making them suitable for CPZ detection in human serum. This provides a novel idea for real-time and in vivo CPZ detection.
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Terapia por Acupuntura , Técnicas Biossensoriais , Nanopartículas Metálicas , Impressão Molecular , Humanos , Clorpromazina , Ouro/química , Cobre/química , Nanopartículas Metálicas/química , Limite de Detecção , Eletrodos , Técnicas EletroquímicasRESUMO
Small-pore Lewis acid zeolites have been showing increasing potential in shape-selective reactions regarding small-molecule conversion. In this study, Sn-CHA with tunable framework Sn contents was facilely prepared via a fluoride-free, seed-assisted interzeolite conversion (IZC) pathway. Commercially available dealuminated USY functioned as the parent sample, and seeding played a vital role in accelerating the transformation process, promoting the target zeolite yield, and guiding the attached-growth pathway. Notably, a proto-zeolite phase with a semi-constructed pore structure was captured during the IZC process, which represents a crucial intermediate stage for developing the complete CHA structure and ensuring a well-defined Sn status. The detailed synthesis mechanism was explored in multiscale by a series of techniques. The obtained Sn-CHA and proto-Sn-CHA exhibited excellent catalytic performance in converting 1,3-dihydroxyacetone to methyl lactate. Proto-Sn-CHA was proven to be a highly effective glucose isomerization catalyst owing to its larger pore size and Lewis acidic nature.
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BACKGROUND: Dysregulation of ubiquitin ligases plays a crucial role in the development and progression of various human tumors. F-box only protein 22 (FBXO22), an F-box E3 ubiquitin ligase, has been reported to participate in diverse aspects of cancer progression. However, the clinical significance and biological function of FBXO22 in pancreatic cancer remain poorly understood. AIMS: This study aimed to investigate the role of FBXO22 in promoting pancreatic cancer growth. METHODS: FBXO22 expression was detected in pancreatic cancer and adjacent normal tissues using qRT-PCR, western blotting, and immunohistochemistry. Ectopic expression and knockdown of FBXO22 were performed to measure the impact on pancreatic cancer cells growth by CCK-8, colony formation, and tumorigenicity assay. Bioinformatics analysis uncovered the potential correlation between FBXO22 and various signaling pathways. Western blotting and immunoprecipitation were performed to identify FBXO22-interacting proteins. RESULTS: We observed that FBXO22 was upregulated in samples obtained from patients with pancreatic cancer compared with its levels in the adjacent normal tissues, and an elevated FBXO22 level was obviously associated with poor prognosis among patients with pancreatic cancer. FBXO22 knockdown impaired pancreatic cancer cell growth both in vitro and in vivo, whereas FBXO22 overexpression accelerated pancreatic cancer cell growth. Furthermore, we found that FBXO22 contributed to pancreatic cancer cell growth by deactivating the Hippo pathway. Mechanistically, FBXO22 directly interacts with and destabilizes the large tumor suppressor 2 (LATS2), which is a critical regulator of the Hippo pathway. Blocking LATS2 leads to the loss of FBXO22-mediated oncogenic effect in pancreatic cancer. CONCLUSIONS: These findings provide new insights into the upstream regulation of the Hippo pathway inactivation in pancreatic cancer growth and identify FBXO22 as a potential therapeutic target for this lethal malignant tumor.
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Proteínas F-Box , Neoplasias Pancreáticas , Humanos , Linhagem Celular Tumoral , Proliferação de Células , Proteínas F-Box/genética , Proteínas F-Box/metabolismo , Via de Sinalização Hippo , Neoplasias Pancreáticas/metabolismo , Neoplasias Pancreáticas/patologia , Proteínas Serina-Treonina Quinases/metabolismo , Receptores Citoplasmáticos e Nucleares/metabolismo , Proteínas Supressoras de Tumor/genética , Proteínas Supressoras de Tumor/metabolismoRESUMO
BACKGROUND: This study aimed to investigate the safety and efficacy of laparoscopic anatomical left hemihepatectomy guided by the middle hepatic vein (MHV) for the treatment of patients with hepatolithiasis who had a history of upper abdominal surgery. METHODS: Retrospective data analysis was performed on patients who underwent laparoscopic left hepatectomy for hepatolithiasis and with previous upper abdominal surgery at the Second Affiliated Hospital of Nanchang University from January 2018 to April 2022. According to the different surgical approaches, patients were divided into laparoscopic anatomical left hepatectomy guided by the MHV group (MHV-AH group) and laparoscopic traditional anatomical left hepatectomy not guided by the MHV group (non-MHV-AH group). RESULTS: This study included 81 patients, with 37 and 44 patients in the MHV-AH and non-MHV-AH groups, respectively. There was no significant difference in the basic information between the two groups. Five cases were converted to laparotomy, and the remaining were successfully completed under laparoscopy. Compared to the non-MHV-AH group, the MHV-AH group had a slightly longer operation time (319.30 min vs 273.93 min, P = 0.032), lower bile leakage rate (5.4% vs 20.5%, P = 0.047), stone residual rate (2.7% vs 20.5%, P = 0.015), stone recurrence rate (5.4% vs 22.7%, P = 0.028), and cholangitis recurrence rate (2.7% vs 22.7%, P = 0.008).There were no significant differences in the results of other observation indices between the groups. CONCLUSIONS: Laparoscopic anatomical left hepatectomy guided by the MHV is safe and effective in the treatment of left hepatolithiasis with a history of upper abdominal surgery. It does not increase intraoperative bleeding and reduces the risk of postoperative bile leakage, residual stones, stone recurrence, and cholangitis recurrence.