Exercise ameliorates lipid droplet metabolism disorder by the PLIN2-LIPA axis-mediated lipophagy in mouse model of non-alcoholic fatty liver disease.

Excessive hepatic lipid droplets (LDs) accumulation-induced lipid metabolism disorder contributes to the development of non-alcoholic fatty liver disease (NAFLD). Exercise is a promising therapeutic strategy for NAFLD. However, the mechanism by which exercise ameliorates NAFLD through regulating the catabolism of hepatic LDs remains unclear. In the present study, we investigated the effect of perilipin2 (PLIN2)-lysosomal acid lipase (LIPA) axis mediating exercise-triggered lipophagy in a high-fat diet (HFD)-induced NAFLD mouse model. Our results showed that exercise could reduce HFD-induced hepatic LDs accumulation and change the expression of lipolysis-related enzymes. Moreover, exercise upregulated the expression of microtubule associated protein 1 light chain 3 (LC3) and autophagy-related proteins, and downregulated sequestosome 1 (P62) expression and promoted autophagosomes formation. Interestingly, exercise downregulated PLIN2 expression, upregulated LIPA expression, and increased the activity of hepatic LIPA and serum levels of LIPA in the NAFLD mouse model. Further mechanistic studies demonstrated that adenosine monophosphate-activated protein kinase (AMPK) activator-5-Aminoimidazole-4-carboxamide ribonucleoside (AICAr) treatment significantly increased mRNA levels and protein expression of LIPA and LC3II and decreased levels of PLIN2 and P62 in palmitic acid (PA)-treated HepG2 cells. PLIN2 silencing and LIPA overexpression notably increased the mRNA level and protein expression of LC3II and decreased the mRNA level and protein expression of p62, respectively. In summary, our findings reveal novel insights into the effect of exercise on improving lipid droplet metabolism disorder in NAFLD. Enhancing the PLIN2-LIPA axis-mediated lipophagy may be one of the key mechanisms involved in NAFLD alleviation by exercise.

Targeting CD24 as a novel immunotherapy for solid cancers.

Cluster of differentiation 24 (CD24), a mucin-like highly glycosylated molecule has been extensively studied as a cancer stem cell marker in a variety of solid cancers. The functional role of CD24 is either fulfilled by combining with ligands or participating in signal transduction, which mediate the initiation and progression of neoplasms. Recently, CD24 was also described as an innate immune checkpoint with apparent significance in several types of solid cancers. Herein, we review the current understanding of the molecular fundamentals of CD24, the role of CD24 in tumorigenesis and cancer progression, the possibility as a promising therapeutic target and summarized different therapeutic agents or strategies targeting CD24 in solid cancers. Video Abstract.

Validation of a deep learning model for traumatic brain injury detection and NIRIS grading on non-contrast CT: a multi-reader study with promising results and opportunities for improvement.

PURPOSE: This study aimed to assess and externally validate the performance of a deep learning (DL) model for the interpretation of non-contrast computed tomography (NCCT) scans of patients with suspicion of traumatic brain injury (TBI). METHODS: This retrospective and multi-reader study included patients with TBI suspicion who were transported to the emergency department and underwent NCCT scans. Eight reviewers, with varying levels of training and experience (two neuroradiology attendings, two neuroradiology fellows, two neuroradiology residents, one neurosurgery attending, and one neurosurgery resident), independently evaluated NCCT head scans. The same scans were evaluated using the version 5.0 of the DL model icobrain tbi. The establishment of the ground truth involved a thorough assessment of all accessible clinical and laboratory data, as well as follow-up imaging studies, including NCCT and magnetic resonance imaging, as a consensus amongst the study reviewers. The outcomes of interest included neuroimaging radiological interpretation system (NIRIS) scores, the presence of midline shift, mass effect, hemorrhagic lesions, hydrocephalus, and severe hydrocephalus, as well as measurements of midline shift and volumes of hemorrhagic lesions. Comparisons using weighted Cohen's kappa coefficient were made. The McNemar test was used to compare the diagnostic performance. Bland-Altman plots were used to compare measurements. RESULTS: One hundred patients were included, with the DL model successfully categorizing 77 scans. The median age for the total group was 48, with the omitted group having a median age of 44.5 and the included group having a median age of 48. The DL model demonstrated moderate agreement with the ground truth, trainees, and attendings. With the DL model's assistance, trainees' agreement with the ground truth improved. The DL model showed high specificity (0.88) and positive predictive value (0.96) in classifying NIRIS scores as 0-2 or 3-4. Trainees and attendings had the highest accuracy (0.95). The DL model's performance in classifying various TBI CT imaging common data elements was comparable to that of trainees and attendings. The average difference for the DL model in quantifying the volume of hemorrhagic lesions was 6.0 mL with a wide 95% confidence interval (CI) of - 68.32 to 80.22, and for midline shift, the average difference was 1.4 mm with a 95% CI of - 3.4 to 6.2. CONCLUSION: While the DL model outperformed trainees in some aspects, attendings' assessments remained superior in most instances. Using the DL model as an assistive tool benefited trainees, improving their NIRIS score agreement with the ground truth. Although the DL model showed high potential in classifying some TBI CT imaging common data elements, further refinement and optimization are necessary to enhance its clinical utility.

Prediction of delayed cerebral ischemia after cerebral aneurysm rupture using explainable machine learning approach.

BACKGROUND: Aneurysmal subarachnoid hemorrhage results in significant mortality and disability, which is worsened by the development of delayed cerebral ischemia. Tests to identify patients with delayed cerebral ischemia prospectively are of high interest. OBJECTIVE: We created a machine learning system based on clinical variables to predict delayed cerebral ischemia in aneurysmal subarachnoid hemorrhage patients. We also determined which variables have the most impact on delayed cerebral ischemia prediction using SHapley Additive exPlanations method. METHODS: 500 aneurysmal subarachnoid hemorrhage patients were identified and 369 met inclusion criteria: 70 patients developed delayed cerebral ischemia (delayed cerebral ischemia+) and 299 did not (delayed cerebral ischemia-). The algorithm was trained based upon age, sex, hypertension (HTN), diabetes, hyperlipidemia, congestive heart failure, coronary artery disease, smoking history, family history of aneurysm, Fisher Grade, Hunt and Hess score, and external ventricular drain placement. Random Forest was selected for this project, and prediction outcome of the algorithm was delayed cerebral ischemia+. SHapley Additive exPlanations was used to visualize each feature's contribution to the model prediction. RESULTS: The Random Forest machine learning algorithm predicted delayed cerebral ischemia: accuracy 80.65% (95% CI: 72.62-88.68), area under the curve 0.780 (95% CI: 0.696-0.864), sensitivity 12.5% (95% CI: -3.7 to 28.7), specificity 94.81% (95% CI: 89.85-99.77), PPV 33.3% (95% CI: -4.39 to 71.05), and NPV 84.1% (95% CI: 76.38-91.82). SHapley Additive exPlanations value demonstrated Age, external ventricular drain placement, Fisher Grade, and Hunt and Hess score, and HTN had the highest predictive values for delayed cerebral ischemia. Lower age, absence of hypertension, higher Hunt and Hess score, higher Fisher Grade, and external ventricular drain placement increased risk of delayed cerebral ischemia. CONCLUSION: Machine learning models based upon clinical variables predict delayed cerebral ischemia with high specificity and good accuracy.

The automatic evaluation of steno-occlusive changes in time-of-flight magnetic resonance angiography of moyamoya patients using a 3D coordinate attention residual network.

Background: Moyamoya disease (MMD) is a rare cerebrovascular occlusive disease with progressive stenosis of the terminal portion of internal cerebral artery (ICA) and its main branches, which can cause complications, such as high risks of disability and increased mortality. Accurate and timely diagnosis may be difficult for physicians who are unfamiliar to MMD. Therefore, this study aims to achieve a preoperative deep-learning-based evaluation of MMD by detecting steno-occlusive changes in the middle cerebral artery or distal ICA areas. Methods: A fine-tuned deep learning model was developed using a three-dimensional (3D) coordinate attention residual network (3D CA-ResNet). This study enrolled 50 preoperative patients with MMD and 50 controls, and the corresponding time of flight magnetic resonance angiography (TOF-MRA) imaging data were acquired. The 3D CA-ResNet was trained based on sub-volumes and tested using patch-based and subject-based methods. The performance of the 3D CA-ResNet, as evaluated by the area under the curve (AUC) of receiving-operator characteristic, was compared with that of three other conventional 3D networks. Results: With the resulting network, the patch-based test achieved an AUC value of 0.94 for the 3D CA-ResNet in 480 patches from 10 test patients and 10 test controls, which is significantly higher than the results of the others. The 3D CA-ResNet correctly classified the MMD patients and normal healthy controls, and the vascular lesion distribution in subjects with the disease was investigated by generating a stenosis probability map and 3D vascular structure segmentation. Conclusions: The results demonstrated the reliability of the proposed 3D CA-ResNet in detecting stenotic areas on TOF-MRA imaging, and it outperformed three other models in identifying vascular steno-occlusive changes in patients with MMD.

Diffusion-weighted imaging and arterial spin labeling radiomics features may improve differentiation between radiation-induced brain injury and glioma recurrence.

OBJECTIVES: To determine whether radiomics features derived from diffusion-weighted imaging (DWI) and arterial spin labeling (ASL) can improve the differentiation between radiation-induced brain injury (RIBI) and tumor recurrence (TR) in glioma patients. METHODS: A total of 4199 radiomics features were extracted from conventional MRI, apparent diffusion coefficient (ADC), and cerebral blood flow (CBF) maps, obtained from 96 pathologically confirmed WHO grade 2~4 gliomas with enhancement after standard treatment. The intraclass correlation coefficient (ICC) was used to test segmentation stability between two doctors. Radiomics features were selected using the Mann-Whitney U test, LASSO regression, and RFE algorithms. Four machine learning classifiers were adopted to establish radiomics models. The diagnostic performance of multiparameter, conventional, and single-parameter MRI radiomics models was compared using the area under the curve (AUC). The models were evaluated in the subsequent independent validation set (n = 30). RESULTS: Eight important radiomics features (3 from conventional MRI, 1 from ADC, and 4 from CBF) were selected. Support vector machine (SVM) was chosen as the optimal classifier. The diagnostic performance of the multiparameter MRI radiomics model (AUC 0.96) was higher than that of the conventional MRI (AUC 0.88), ADC (AUC 0.91), and CBF (AUC 0.95) radiomics models. For subgroup analysis, the multiparameter MRI radiomics model showed similar performance, with AUCs of 0.98 in WHO grade 2~3 and 0.96 in WHO grade 4. CONCLUSION: The incorporation of noninvasive DWI and ASL into the MRI radiomics model improved the diagnostic performance in differentiating RIBI from TR; ASL, especially, played a significant role. KEY POINTS: • The multiparameter MRI radiomics model was superior to the conventional MRI radiomics model in differentiating glioma recurrence from radiation-induced brain injury. • Diffusion and perfusion MRI could improve the ability of the radiomics model in predicting the progression in patients with glioma. • Arterial spin labeling played an important role in predicting glioma progression using radiomics models.

Multi-Modal Co-Learning for Liver Lesion Segmentation on PET-CT Images.

Liver lesion segmentation is an essential process to assist doctors in hepatocellular carcinoma diagnosis and treatment planning. Multi-modal positron emission tomography and computed tomography (PET-CT) scans are widely utilized due to their complementary feature information for this purpose. However, current methods ignore the interaction of information across the two modalities during feature extraction, omit the co-learning of the feature maps of different resolutions, and do not ensure that shallow and deep features complement each others sufficiently. In this paper, our proposed model can achieve feature interaction across multi-modal channels by sharing the down-sampling blocks between two encoding branches to eliminate misleading features. Furthermore, we combine feature maps of different resolutions to derive spatially varying fusion maps and enhance the lesions information. In addition, we introduce a similarity loss function for consistency constraint in case that predictions of separated refactoring branches for the same regions vary a lot. We evaluate our model for liver tumor segmentation using a PET-CT scans dataset, compare our method with the baseline techniques for multi-modal (multi-branches, multi-channels and cascaded networks) and then demonstrate that our method has a significantly higher accuracy ( ) than the baseline models.

Retracted Article: Macrophage-derived exosomes mediate osteosarcoma cell behavior by activating AKT signaling.

Osteosarcoma is the most common type of bone tumor, which severely threatens the health of adolescents and young adults. Tumor-infiltrating macrophages have been shown to mediate cancer progression via extracellular vesicles. However, their potential mechanisms in osteosarcoma progression and in drug-resistance are still not yet known. The macrophage cell line THP1 was stimulated by phorbol myristate acetate (PMA) to secrete exosomes. The exosomes isolated from THP1 were characterized via transmission electron microscopy (TEM), nanoparticle tracking analysis (NTA) and by a western blot. Cell proliferation was determined using CCK-8. A transwell assay and flow cytometry were conducted to detect cell migration and apoptosis, respectively. The expression levels of AKT and its phosphorylation status were determined using a western blot. PMA-treated activated THP1 cells secreted an abundance of exosomes with the characteristics of being less than 200 nm in diameter, and showing the robust expression of exosome markers CD63 and CD81. The THP1-derived exosomes promoted cell proliferation, migration and drug-resistance to the chemical drug docetaxel in both osteosarcoma cell lines MG63 and 143B. The inhibition of the generation of exosomes by the knockdown of ALIX clearly suppressed the cell proliferation, migration and drug-resistance. Mechanistically, the THP1-derived exosomes activated AKT signaling by inducing the increased expression of the phosphorylated AKT at serine 473 (p-AKT). The AKT inhibitor MK2206 significantly abolished exosome-mediated cell proliferation and drug-resistance in osteosarcoma cells. In summary, our data demonstrated that macrophage-derived exosomes promoted osteosarcoma progression and drug-resistance by activating AKT signaling that could be used as a potential molecular target for osteosarcoma treatment.

A Dataset of Pulmonary Lesions With Multiple-Level Attributes and Fine Contours.

Lung cancer is a life-threatening disease and its diagnosis is of great significance. Data scarcity and unavailability of datasets is a major bottleneck in lung cancer research. In this paper, we introduce a dataset of pulmonary lesions for designing the computer-aided diagnosis (CAD) systems. The dataset has fine contour annotations and nine attribute annotations. We define the structure of the dataset in detail, and then discuss the relationship of the attributes and pathology, and the correlation between the nine attributes with the chi-square test. To demonstrate the contribution of our dataset to computer-aided system design, we define four tasks that can be developed using our dataset. Then, we use our dataset to model multi-attribute classification tasks. We discuss the performance in 2D, 2.5D, and 3D input modes of the classification model. To improve performance, we introduce two attention mechanisms and verify the principles of the attention mechanisms through visualization. Experimental results show the relationship between different models and different levels of attributes.

Applications of Deep Learning to Neuro-Imaging Techniques.

Many clinical applications based on deep learning and pertaining to radiology have been proposed and studied in radiology for classification, risk assessment, segmentation tasks, diagnosis, prognosis, and even prediction of therapy responses. There are many other innovative applications of AI in various technical aspects of medical imaging, particularly applied to the acquisition of images, ranging from removing image artifacts, normalizing/harmonizing images, improving image quality, lowering radiation and contrast dose, and shortening the duration of imaging studies. This article will address this topic and will seek to present an overview of deep learning applied to neuroimaging techniques.

Batf3-dependent CD8α+ Dendritic Cells Aggravates Atherosclerosis via Th1 Cell Induction and Enhanced CCL5 Expression in Plaque Macrophages.

Dendritic cells (DCs) play an important role in controlling T cell-mediated adaptive immunity in atherogenesis. However, the role of the basic leucine zipper transcription factor, ATF-like 3 (Batf3)-dependent CD8α+ DC subset in atherogenesis remains unclear. Here we show that Batf3-/-Apoe-/- mice, lacking CD8α+ DCs, exhibited a significant reduction in atherogenesis and T help 1 (Th1) cells compared with Apoe-/- controls. Then, we found that CD8α+ DCs preferentially induce Th1 cells via secreting interleukin-12 (IL-12), and that the expression of interferon-gamma (IFN-γ)or chemokine (C-C motif) ligand 5 (CCL5) in aorta were significantly decreased in Batf3-/-Apoe-/- mice. We further demonstrated that macrophages were the major CCL5-expressing cells in the plaque, which was significantly reduced in Batf3-/-Apoe-/- mice. Furthermore, we found CCL5 expression in macrophages was promoted by IFN-γ. Finally, we showed that Batf3-/-Apoe-/- mice displayed decreased infiltration of leukocytes in the plaque. Thus, CD8α+ DCs aggravated atherosclerosis, likely by inducing Th1 cell response, which promoted CCL5 expression in macrophages and increased infiltration of leukocytes and lesion inflammation.

Exome Sequencing and Gene Prioritization Correct Misdiagnosis in a Chinese Kindred with Familial Amyloid Polyneuropathy.

Inherited neuropathies show considerable heterogeneity in clinical manifestations and genetic etiologies, and are therefore often difficult to diagnose. Whole-exome sequencing (WES) has been widely adopted to make definite diagnosis of unclear conditions, with proven efficacy in optimizing patients' management. In this study, a large Chinese kindred segregating autosomal dominant polyneuropathy with incomplete penetrance was ascertained through a patient who was initially diagnosed as Charcot-Marie-Tooth disease. To investigate the genetic cause, forty-six living family members were genotyped by SNP microarrays, and one confirmed patient was subject to WES. Through systematic computational prioritization, we identified a missense mutation c.G148T in TTR gene which results in a p.V50L substitution known to cause transthyretin-related familial amyloid polyneuropathy. Co-segregation analysis and clinical follow-up confirmed the new diagnosis, which suggested new therapeutic options to the patients and informed high risk family members. This study confirms WES as a powerful tool in translational medicine, and further demostrates the practical utility of gene prioritization in narrowing the scope of causative mutation.

Outcomes after endovascular treatment for anterior circulation stroke presenting as wake-up strokes are not different than those with witnessed onset beyond 8†hours.

OBJECTIVE: Previous studies have suggested that patients with wake-up stroke (WUS) may have superior outcomes compared with patients with a witnessed late time of onset after revascularization. We sought to test this hypothesis in patients with anterior circulation large vessel occlusion stroke (ACLVOS) treated with endovascular therapy beyond 8 h from time last seen well (TLSW). METHODS: A single center retrospective review of a prospectively acquired database of consecutive patients was performed to identify patients presenting beyond 8 h of TLSW with radiographic evidence of ACLVOS, small core, and large penumbra who subsequently underwent endovascular treatment. RESULTS: We identified 206 patients. Patients were divided into two groups: (1) patients with WUS (38%, n=78) and (2) patients with witnessed onset beyond 8 h (62%, n=128). The groups were similar in age, baseline National Institutes of Health Stroke Scale score, TLSW to reperfusion, baseline infarct volume, and rate of successful recanalization. Rates of good outcome (modified Rankin Scale score of 0-2 at 90 days, 43% vs. 50%, p=0.3), parenchymal hematoma (9% vs. 5.5%, p=0.3), and final infarct volume (75.2 vs. 61.4 mL, p=0.6) were comparable. Multivariate analysis identified age (OR=0.95, 95% CI 0.91 to 0.99, p<0.042), successful recanalization (OR 6.0, 95% CI 1.5 to 23.5, p=0.009), and final infarct volume (OR 0.98, 95% CI 0.97 to 0.99, p<0.001) but not mode of presentation as predictors of favorable outcomes. CONCLUSIONS: Rates of good outcomes, parenchymal hematoma, and final infarct volumes following endovascular treatment may not be different in patients with WUS compared with patients with witnessed onset of symptoms beyond 8 h.

Comparison of restrictive and liberal transfusion strategy on postoperative delirium in aged patients following total hip replacement: a preliminary study.

Few studies have examined the association between perioperative blood transfusion and postoperative delirium (POD) in aged patients undergoing total hip replacement surgery. In this prospective study, 186 patients older than 65 years undergoing elective unilateral total hip replacement surgery were enrolled. Of those, 94 patients were randomly assigned to the restrictive strategy transfusion strategy group, in which red blood cells were transfused in order to maintain 10.0 g/dL>hemoglobin≧8.0 g/dL. Ninety-two patients were randomly assigned to the liberal transfusion strategy group, in which red blood cells were transfused in order to maintain hemoglobin≧10.0 g/dL. POD was diagnosed by confusion assessment method. The baseline characteristics of patients, the length of hospital stay, the incidence of POD, myocardial infarction, stroke, wound infection, pulmonary embolism, and the transfusion volume were recorded. No difference was observed in the baseline characteristics, the length of hospital stay, and the incidence of POD, myocardial infarction, stroke, wound infection, and pulmonary embolism between the two groups (P>0.05). The proportion of patients transfused with red blood cell and frozen plasma was decreased in the restrictive transfusion group compared with the liberal transfusion group (P<0.05). In conclusion, restrictive transfusion does not influence the incidence of POD but reduces blood transfusion. Thus, restrictive transfusion may serve as an effective and safe strategy for aged patients following total hip replacement.

[Design of flap using eight-point-location method and clinical application].

OBJECTIVE: To introduce a new method of flap design and to investigate the feasibility of the clinical application. METHODS: Between April 2006 and November 2009, 89 patients with skin and soft tissue defects were treated. There were 47 males and 42 females with an average age of 36 years (range, 16-67 years). The injuries were caused by machine crush (38 cases), electric saw (16 cases), electricity (8 cases), traffic accident (18 cases), rolling machine (3 cases), and crash of heavy object (6 cases). The locations were forearm in 4 cases, palm in 23 cases, finger in 41 cases, lower leg in 7 cases, and dorsum of foot in 14 cases. All the cases complicated by exposure of tendons or bones. The time from injury to hospitalization was 30 minutes to 5 days (mean, 3 hours). The areas of skin and soft tissue defect ranged from 2.0 cm x 1.5 cm to 26.0 cm x 18.0 cm. The wounds were repaired with the pedicle flaps in 72 cases and the free flaps in 17 cases. All the flaps were designed with eight-point-location method. A trapezoid was made in the raw surface and the four vertexes of the trapezoid were on the edge of the raw surface. The exterior points of the heights of arciforms were made on the edge of the raw surface too. The eight points were the labelling points. The top width, the bottom width, the height of the trapezoid, and the heights of the arciforms could be measured. The above numerus were expanded 5%-10%. The expanded numerus were the corresponding numerus of the skin flap. The size of flaps ranged from 2.2 cm x 1.7 cm to 28.5 cmx 19.5 cm. The donor sites were closed directly in 17 cases, and repaired with skin grafts in 72 cases. RESULTS: All the flaps were successfully dissected according to flap design. When the flaps were transplanted to the wounds, tension of the flaps was appropriate. All the flaps and skin grafts survived. The wounds and incisions at donor sites healed by first intention. Eighty-nine patients were followed up 6 to 26 months (mean, 20 months). The texture, appearance, flexibility, and function of the flaps were satisfactory, and no complication occurred. The sensory restoration of the pedicle flaps were graded as S3-S4. CONCLUSION: It is an ideal and simple method to design flap using eight-point-location method. The flaps are precise in the figure and area.

Cannabinoid receptor-2 selective antagonist negatively regulates receptor activator of nuclear factor kappa B ligand mediated osteoclastogenesis.

BACKGROUND: The cannabinoid receptor-2 (CB2) is important for bone remodeling. In this study, we investigated the effects of CB2 selective antagonist (AM630) on receptor activator of nuclear factor kappa B (RANK) ligand (RANKL) induced osteoclast differentiation and the underlying signaling pathway using a monocyte-macrophage cell line-RAW264.7. METHODS: RAW264.7 was cultured with RANKL for 6 days and then treated with AM630 for 24 hours. Mature osteoclasts were measured by tartrate-resistant acid phosphatase (TRAP) staining using a commercial kit. Total ribonucleic acid (RNA) was isolated and real-time reverse transcriptase-polymerase chain reaction (RT-PCR) was done to examine the expression of RANK, cathepsin K (CPK) and nuclear factor kappa B (NF-κB). The extracellular signal-regulated kinase (ERK), phosphorylation of ERK (P-ERK) and NF-κB production were tested by Western blotting. The effect of AM630 on RAW264.7 viability was determined using the 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazoliumbromide (MTT) assay. RESULTS: AM630 did not affect the viability of RAW264.7. However, this CB2 selective antagonist markedly inhibited osteoclast formation and the inhibition rate was dose-dependent. The dose of ≥ 100 nmol/L could reduce TRAP positive cells to the levels that were significantly lower than the control. AM630 suppressed the expression of genes associated with osteoclast differentiation and activation, such as RANK and CPK. An analysis of a signaling pathway showed that AM630 inhibited the RANKL-induced activation of ERK, but not NF-κB. CONCLUSION: AM630 could inhibit the osteoclastogenesis from RAW264.7 induced with RANKL.

[Application of the island flap at the dorsum of the middle phalange with the pedicel of the digital proper artery].

OBJECTIVE: To explore a method for the treatment of the skin defects at the distal phalanges of 2-5th fingers. METHODS: The island flap at the dorsum of the middle phalange was designed with the pedicle of dorsal branches from the digital proper artery. When the flap was used to repair defect at finger pulp, the dorsal branch of the digital proper nerve in the flap was kept to be anastomosed to the digital proper nerve at the recipient finger. From Feb. 2005 to May. 2010, 54 cases with skin defects at the distal phalanges of 61 fingers were treated with the flap, including 35 defects at finger pulp and 26 defects at finger tip. RESULTS: The maximum size of defects and flaps was 2.2 cm x 2.5 cm and 2.4 cm x 2.7 cm, respectively. 61 flaps survived completely. Blister was happened in 3 flaps 2 days after operation, which healed spontaneously without necrosis. 54 cases were followed up for 5 to 22 months (average, 11 months). The flaps had good texture and color match with normal sensation (grade S4). The 2-point discrimination distance was 6-9 mm. The interphalangeal joint had normal movement. CONCLUSIONS: The island flap at the dorsum of the middle phalange is an ideal method for the skin defect at the distal phalange of finger.

Protection against titanium particle induced osteolysis by cannabinoid receptor 2 selective antagonist.

Osteolysis and subsequent aseptic loosening are the most common causes of failure of total joint arthroplasty. Osteolysis is initiated by inflammatory response to wear debris, resulting in localized, osteoclastic peri-implant bone loss. However, there were no effective measures for prevention and treatment of periprosthetic osteolysis. The aim of the current study was to determine whether CB2 selective antagonist (AM630) inhibits wear debris-induced osteolysis in a murine osteolysis model. Titanium (Ti) particles were introduced into established air pouches on BALB/c mice, followed by implantation of calvaria bone from syngeneic littermates. AM630 was given to mice intraperitoneally 2 days before Ti particles introduction and maintained until the sacrifice of the mice. Mice without drug treatment, as well as mice injected with saline alone, were included. Each group contains 10 mice. Pouch tissues were harvested 14 days after bone implantation for histological and molecular analysis. Ti particles stimulation significantly increased CB2 expression. However, less CB2 was observed in AM630 treatment group. AM630 inhibited Ti particle-induced osteolysis associated gene activity of RANK, RANKL and CPK, and diminished RANKL expression in Ti particle stimulated pouches. AM630 markedly reduced the number of TRAP+ cells in pouch tissues. In conclusion, this study provides the evidence that blockage of CB2 with AM630 can markedly reduce Ti particle induced osteolysis in a murine air pouch model. This finding points to the possibility that CB2 selective antagonists like AM630 may have potential value for prevention and treatment of wear particle induced osteolysis.

Kinetic thermal response and damage in laser coagulation of tissue.

BACKGROUND AND OBJECTIVES: Laser induced interstitial coagulation has become a method of treating different types of tumors. Theoretical modeling and analysis may be used to better understand the complex process involved in the laser coagulation and optimized the dosimetry of laser thermotherapy. STUDY DESIGN/MATERIALS AND METHODS: A full dynamic theoretical model was developed to simulate the dynamic evolution of coagulation in tissue, which accounted for the dynamics of the temperature and damage dependence of optical properties, thermal properties, and blood-perfusion rate. The simulation of the temperature distribution, coagulation depth and its hysteresis during laser thermotherapy for full-dynamic model are compared with the calculations from other models. RESULTS: Increased scattering in the near surface of applicator prevents light penetration into deeper region. Moreover, rise in temperature increases both blood flow at the periphery of coagulation region and thermal properties, which reduces the damage depth and its hysteresis. It results in a considerable overestimation of the temperature distribution and damage depth ignoring the dynamic of optical properties. The coagulation would be limited in a smaller region and there is no hysteresis if blood perfusion is regarded as a constant. In contrast, the hysteresis is overestimated if blood perfusion is ignored. Ignoring the dynamics of thermal parameters, there is also overestimation of the rise in temperature and damage depth. CONCLUSIONS: Mathematical modeling techniques that simulate laser coagulation may not provide reliable information unless they take into account these dynamic parameters.