The main treatment methods of liver cancer include surgical resection,TACE,ablation,immunotherapy and liver transplantation,etc.Ablation promotes the death of liver cancer cells to achieve the purpose of anti-tumor.Immunotherapy can reactivate immune cells and generate new immune responses through corresponding pathways,so as to recognize and eliminate liver cancer cells.Combining ablation can synergistically enhance anti-tumor immune effect of immunotherapy for liver cancer.The research progresses of ablation combined with immunotherapy for liver cancer were reviewed in this article.

The main treatment methods of liver cancer include surgical resection,TACE,ablation,immunotherapy and liver transplantation,etc.Ablation promotes the death of liver cancer cells to achieve the purpose of anti-tumor.Immunotherapy can reactivate immune cells and generate new immune responses through corresponding pathways,so as to recognize and eliminate liver cancer cells.Combining ablation can synergistically enhance anti-tumor immune effect of immunotherapy for liver cancer.The research progresses of ablation combined with immunotherapy for liver cancer were reviewed in this article.

Objective To investigate the relationship between the expression of programmed death ligand 1(PD-L1)and hypoxia inducible factor-1α(HIF-1 α)with the clinical pathological characteristics and prognosis of gastric cancer patients.Methods The cancer tissues of 100 gastric cancer patients who underwent radical gastrectomy at the First Hospital of Handan City from July 2019 to July 2020 were selected as the research subjects,and their adjacent tissues(normal tissues ≥ 5 cm from the cancer tissues)were as the control group.Immunohistochemical detection of PD-L1 and HIF-1 α was performed by SP method.Spearman correlation analysis was used to analyze PD-L1 and HIF-1 α in gastric cancer tissues.Kaplan-Meier method was used to analyze the 3-year survival relationship of gastric cancer patients.The influencing factors of prognosis and death in patients with gastric cancer were analyzed by univariate and multivariate Cox regression.Results Among 100 gastric cancer patients,52 were PD-L1 positive and 48 were negative;67 were HIF-1 α positive and 33 were HIF-1 α negative,the positive expression rates of PD-L1 and HIF-1α in gastric cancer tissues were 52.00％and 67.00％,respectively,which were obviously higher than those in adjacent tissues(11.00％、18.00％),the difference was statistically significant(P＜0.05).Spearman correlation analysis showed that the expression of PD-L1 was positively correlated with that of HIF-1α in gastric cancer tissues(r=0.730,P＜0.001).The expressions of PD-L1 and HIF-1α in patients with gastric cancer were correlated with TNM stage,lymph node metastasis and local invasion(P＜0.05).The 3-year overall survival rate of gastric cancer patients was 48.00％after surgery,and the 3-years survival rate of patients with positive expression of PD-L1 and HIF-1α were 28.85％and 31.34％,which were lower than those of patients with negative expression of PD-L1 and HIF-1α(68.75％and 81.82％)(Log rank x2=25.155,P＜0.001.Log rank x2=24.552,P＜0.001).Moreover,positive expression of PD-L1 and HIF-1α,TNM staging of Ⅲ-Ⅳ,lymph node metastasis,and local infiltration were independent risk factors for prognosis and death in gastric cancer patients(P＜0.05).Conclusion Both PD-L1 and HIF-1α are highly expressed in cancer tissues of gastric cancer patients,and they are positively correlated.They are also associated with clinical pathological features such as TNM staging,lymph node metastasis,and poor prognosis.

The objectification of facial diagnosis has been developed through recent years and has become a multidisciplinary research topic.However,many studies are still limited to the adjustment of algorithms and the design of data collection environment and equipments,few studies focus on facial diagnosis zoning.The purpose of this paper is to discuss the problems in the current research literature on machine learning-based intelligent TCM facial diagnosis zoning to build a foundation for subsequent related research.The study uses bibliometric methods and text analysis to clarify and analyze the current intelligent TCM facial diagnosis zoning methods,which mainly include facial feature point-based,facial feature block-based and complete face-based method;then by analyzing the influencing factors of facial diagnosis zoning research and summarizing the common machine learning algorithms,the advantages and disadvantages of different machine learning algorithms and the corresponding common facial diagnosis zoning methods are obtained;Finally,we discuss three aspects of the current phase of facial diagnosis zoning research:dataset construction,advantages of deep learning,and embodiment of facial diagnosis theory.

BACKGROUND: Patellofemoral joint (PFJ) degeneration has traditionally been regarded as a contraindication to unicompartmental knee arthroplasty (UKA). More recently, some researchers have proposed that PFJ degeneration can be ignored in medial UKA, and others have proposed that this change should be reviewed in PFJ degenerative facets and severity. This study aimed to systematically evaluate the effect of PFJ degeneration on patient-reported outcome measures (PROMs) and revision rates after medial UKA. METHODS: Electronic databases (PubMed, Embase, Web of Science, etc.) were searched for studies assessing the influence of PFJ degeneration on medial UKA. A random-effects meta-analysis was conducted for the Oxford knee score (OKS), Knee society score (KSS), and revision rates and stratified by PFJ degenerative facets (medial/lateral/trochlear/unspecified), severe PFJ degeneration (bone exposed), and bearing type (mobile/fixed). Heterogeneity was assessed by the Cochran Q test statistic and chi-squared tests with the I-squared statistic. RESULTS: A total of 34 articles with 7007 knees (2267 with PFJ degeneration) were included (5762 mobile-bearing and 1145 fixed-bearing and 100 unspecified). Slight to moderate degenerative changes in the medial and trochlear facets did not decrease the OKS and KSS, and only lateral facets significantly decreased the OKS (mean difference [MD] = -2.18, P   <  0.01) and KSS (MD = -2.61, P   <  0.01). The severity degree of PFJ degeneration had no additional adverse effect on the OKS, KSS, or revision rates. For mobile-bearing UKA, only lateral PFJ degeneration significantly decreased the OKS (MD = -2.21, P  < 0.01) and KSS (MD = -2.44, P  < 0.01). For fixed-bearing UKA, no correlation was found between PROMs/revision rates and PFJ degeneration. CONCLUSION For medial mobile-bearing UKA, slight to moderate degenerative changes in the PFJ, except lateral facet, did not compromise PROMs or revision rates. For medial fixed-bearing UKA, although it might not be conclusive enough, PROMs or revision rates were not adversely affected by PFJ degeneration (regardless of the facet).
Humans ; Arthroplasty, Replacement, Knee ; Patellofemoral Joint/surgery* ; Treatment Outcome ; Osteoarthritis, Knee/surgery* ; Knee Prosthesis ; Bone Diseases ; Knee Joint/surgery* ; Retrospective Studies

Objective:To evaluate the value of dual-layer spectral detector CT (DLSDCT) in precise radiotherapy for central lung cancer (CLC) complicated with atelectasis.Methods:Clinical and imaging data (including DLSDCT, PET-CT, and radiotherapy simulation CT images) of 26 patients with pathologically confirmed CLC accompanied by atelectasis from the Third Affiliated Hospital of Shandong First Medical University and Shandong Cancer Hospital were analyzed retrospectively. There were 21 males and 5 females, aged 36-82 years. Two physicians assessed CLC identifiability on DLSDCT, PET-CT, and simulation localization CT images, respectively, and outlined the gross tumor volume (GTV) and measured GTV values (GTV DLSDCT, GTV PET-CT, GTV CT). Paired-sample Friedman test was used to compare the differences in GTV of the three images, and the SNK test with Bonferroni correction was used for a two-way comparison. The intra-class correlation coefficient (ICC) was used to compare the agreement of measured GTV between 2 physicians. Results:The differentiation rates on PET-CT, DLSDCT, and simulation CT images were 100% (26/26), 80.77% (21/26), and 11.54% (3/26), respectively. The differentiation rate of CLC on DLSDCT images was significantly higher than that on simulation CT images (χ 2=16.06, P<0.001). GTV CT, GTV PET-CT, and GTV DLSDCT measured on simulation localization CT images, PET-CT images, and DLSDCT images were 58.75 (22.57, 86.17) cm 3, 47.34 (18.13, 69.25) cm 3, and 51.40 (18.87, 71.31) cm 3, respectively, with statistically significant differences (χ 2=44.99, P<0.001). Both GTV DLSDCT and GTV PET-CT were significantly smaller than GTV CT (χ 2=4.23, 6.59, Bonferroni corrected P<0.001), and there was no significant difference between GTV DLSDCT and GTV PET-CT (χ 2=2.36, Bonferroni corrected P=0.055). The agreement between the two physicians was good for GTV values measured on both DLSDCT and PET-CT (ICC=0.86, 0.89). Conclusions:On DLSDCT images, most CLC and atelectasis can be identified. Compared to simulation localization CT, the tumor target areas outlined on DLSDCT are closer to PET-CT, and the tumor volumes outlined by different physicians are more consistent.

Background::Although various therapies have been developed to treat malalignment in osteoarthritic knees, the pattern of malalignment progression is still unclear. This study aimed to identify homogeneous subgroups with distinct trajectories of malalignment progression in subjects with symptomatic knee osteoarthritis (KOA) and to determine corresponding risk factors.Methods::Eight-year follow-up (from 2004 to 2012) data on 1252 participants with symptomatic KOA from the Osteoarthritis Initiative were included. Varus/valgus angle progression was characterized by group-based trajectory models. Time-varying covariates were introduced into the model to investigate how they affected trajectories. Multinomial logistic regression for trajectory group membership was applied to ascertain risk factors.Results::Five subgroups were identified. Participants in the varus worsening trajectory ( n = 166) or valgus worsening trajectory ( n = 118) proceeded to worsen malalignment over time. The neutral trajectory ( n = 378), varus stable trajectory ( n = 328), and valgus stable trajectory ( n = 262) maintained close to the initial varus/valgus angle over 8 years. Higher baseline Kellgren and Lawrence grade (odds ratio [OR] = 4.35, P < 0.001 for varus; OR= 3.85, P < 0.001 for valgus) and "severe" baseline malalignment (OR = 13.57, P < 0.001 for varus; OR = 23.04, P < 0.001 for valgus) were risk factors for worsening trajectories. The cutoff point of the baseline varus/valgus angle to discriminate between stable or worsening trajectory was -4.5° for varus and 3.6° for valgus. Conclusions::This study identified the malalignment progression pattern — minor malalignment (-4.5° to +3.6°) tends to remain stable, while major baseline malalignment is likely to progress. This provides a reference for therapy to prevent malalignment from deteriorating and emphasizes the necessity of determining the trigger factors for malalignment onset.

Paeonol has inhibitory effect on a variety of tumor cells, whereas cadherin is a kind of glycoprotein that is associated with the occurrence and development of different tumor.In this study, the interactions of paeonol and E-cadherin have been investigated by fluorescence spectrometry and atomic force microscopy (AFM).Fluorescence spectrometry results revealed that the addition of paeonol significantly quenched the fluorescence of E-cadherin.Based on the results of the quenching constant, it was inferred that the interaction of paeonol and E-cadherin was a static quenching process.The thermodynamic parameters ΔH and ΔS were calculated to be -4.3×10.5 J/mol and -1.3×10.3 J/(mol·K), respectively, which proved the involvement of weak interactive forces such as hydrogen bond van der Waals force.AFM results revealed that cadherin molecules were assembled into the long-chain structure.The addition of paeonol could significantly disrupt these assembling structures into short chains, which could be ascribed to the damage of the interdigitation model from the adjacent cadherin molecules.All these results reveal that cadherin is an important target of paeonol to modulate its activity.

An enhance matrix removal ( EMR) QuEChERS method for simultaneous determination of 22 triazine herbicide residuals such as atrazine, propazine, terbumeton, and desmetryn in corn was established and validated. The corn samples were initially extracted with acetonitrile ( MeCN ) in high-speed homogenization, and the targeted pesticides were prepared using EMR-Lipid (Enhanced matrix removal-lipid) method to clean-up and EMR-Polish to salt out, separated on a Kinetex XB-C18 with acetonitrile and 0. 1%formic acid aqueous as eluant, and then detected by UFLC-MS / MS under positive ( ESI+ ) electrospray ionization and MRM models. The average recoveries of 22 herbicides were in the range of 72% -105% at the spiked level of 5, 10 and 20 μg / kg. The relative standard deviations were less than 15% . In the method validation, correlation coefficients were higher than 0. 993 with the linear range from 1. 0 μg / L to 50 μg / L. The qualitative analysis and quantitative analysis were investigated by UFLC-MS / MS and matrix-matched calibration curves. The results showed that EMR QuEChERS combined with UFLC-MS / MS purification method was rapid, accurate and sensitive for the determination of 22 triazine herbicides residues in corn.

Mutations in LR RK2 (Leucine rich repeat kinase 2) are a major cause of Parkinson's disease (PD). We and others reported recently that expression of the pathogenic gainof-function mutant form of LRRK2, LRRK2 G2019S, induces mitochondrial fission in neurons through DLP1. Here we provide evidence that expression of LRRK2 G2019S stimulates mitochondria loss or mitophagy. We have characterized several LRRK2 interacting proteins and found that LRRK2 interacts with ULK1 which plays an essential role in autophagy. Knockdown of either ULK1 or DLP1 expression with shRNAs suppresses LRRK2 G2019S expression-induced mitochondrial clearance, suggesting that LRRK2 G2019S expression induces mitochondrial fission through DLP1 followed by mitophagy via an ULK1 dependent pathway. In addition to ULK1, we found that LRRK2 interacts with the endogenous MKK4/7, JIP3 and coordinates with them in the activation of JNK signaling. Interestingly, LRRK2 G2019S-induced loss of mitochondria can also be suppressed by 3 different JNK inhibitors, implying the involvement of the JNK pathway in the pathogenic mechanism of mutated LRRK2. Thus our findings may provide an insight into the complicated pathogenesis of PD as well as some clues to the development of novel therapeutic strategies.
Amino Acid Substitution ; Autophagosomes ; metabolism ; pathology ; Autophagy-Related Protein-1 Homolog ; chemistry ; genetics ; metabolism ; GTP Phosphohydrolases ; antagonists & inhibitors ; genetics ; metabolism ; Gene Knockdown Techniques ; HeLa Cells ; Humans ; Intracellular Signaling Peptides and Proteins ; chemistry ; genetics ; metabolism ; Leucine-Rich Repeat Serine-Threonine Protein Kinase-2 ; chemistry ; genetics ; metabolism ; MAP Kinase Signaling System ; Microtubule-Associated Proteins ; antagonists & inhibitors ; genetics ; metabolism ; Mitochondrial Degradation ; genetics ; physiology ; Mitochondrial Proteins ; antagonists & inhibitors ; genetics ; metabolism ; Mutant Proteins ; chemistry ; genetics ; metabolism ; Mutation ; Parkinson Disease ; genetics ; metabolism ; pathology ; Protein Interaction Domains and Motifs ; Recombinant Proteins ; chemistry ; genetics ; metabolism