Association of DOK3 and infiltrated tumor-associated macrophages with risk for the prognosis of Porphyromonas gingivalis-infected oral cancer: a 12-year data analysis of 200 patients from a tertiary teaching hospital, Urumqi, China.

BACKGROUND: While there is an understanding of the association between the expression of Porphyromonas gingivalis (P. gingivalis) and prognosis of oral squamous cell carcinoma (OSCC), significance specially to address the relevance between different immunohistochemical intensities of P. gingivalis and tumor-associated macrophages (TAMs) in OSCC tissue and related clinicopathologic characteristics has not been well investigated. The present study aimed to investigate the pathological features related to M2-TAM in P. gingivalis-infected OSCC and ascertain its clinical relevance with patients' prognosis. METHODS: A prospective cohort study was designed to comparatively analyze 200 patients from June 2008 to June 2020. Bioinformatics analyses were implemented to identify DOK3 as a key molecule and to appraise immunocyte infiltration using Gene Expression Omnibus and The Cancer Genome Atlas databases. Immunohistochemical evaluation was performed to analyze the association between the expression levels of P. gingivalis, DOK3, and M2-TAM and clinicopathological variables using Fisher's exact test or Pearson's chi-square test. Cox analysis was used to calculate hazard ratios (HR) with corresponding 95% confidence interval (CI) for various clinicopathological features. The Kaplan-Meier approach and log-rank test were used to plot the survival curves. RESULTS: The expression level of P. gingivalis was positively associated with DOK3 and M2-TAMs expression level (P < 0.001). Parameters, including body mass index, clinical stage, recurrence, tumor differentiation, and P. gingivalis, DOK3, and M2-TAM immunoexpression levels, affected the prognosis of patients with OSCC (all P < 0.05). In addition, P. gingivalis (HR = 1.674, 95%CI 1.216-4.142, P = 0.012), DOK3 (HR = 1.881, 95%CI 1.433-3.457, P = 0.042), and M2-TAM (HR = 1.649, 95%CI 0.824-3.082, P = 0.034) were significantly associated with the 10-year cumulative survival rate. CONCLUSIONS: Elevated expression of P. gingivalis and DOK3 indicates M2-TAM infiltration and unfavorable prognosis of OSCC, and could be considered as three novel independent risk factors for predicting the prognosis of OSCC.

Two Pathological Fractures in a Patient with Chronic Abnormalities in Serum Markers Following Two Liver Transplantations: A Case Report and Literature Review.

Bone disease is a common complication following liver transplantation, often overlooked in clinical practice. Clinical diagnosis of post-liver transplantation bone disease is challenging, and there have been few case report in the literature. This case report presents a patient who underwent two liver transplant surgeries, exhibited good daily activity, and did not display typical clinical symptoms such as fatigue, bone pain, or spinal deformities associated with prolonged sitting or standing. However, within the fifth year after the second liver transplant, the patient experienced two consecutive fractures. In March 2023, the patient underwent the first bone density test, which revealed osteoporosis. This case highlights the fact that severe fractures after liver transplantation may not necessarily be accompanied by typical symptoms of bone disease. Without timely examination and early prevention, serious consequences may arise. Therefore, this condition requires attention, proactive prevention, early detection, and timely treatment. Additionally, a retrospective analysis of the patient's previous laboratory data revealed persistent abnormalities in serum markers such as hypocalcemia and elevated alkaline phosphatase levels after liver transplantation, emphasizing the importance of monitoring these serum markers.

A comparative evaluation of child health care in China using multicriteria decision analysis methods.

Child health is an important public health issue in China and the Chinese government always attached great importance to child health care. With the implementation of a series of medical and health reforms in China in recent decades, the status of child health improved year by year. Objectives This study aims to comprehensively evaluate if the measures implemented in the medical and health reforms effectively promoted the development of Chinese child health care in recent years and provide theoretical support for future decision-making on the policies of child health care in China. Methods A total of six indicators were selected from the China Health Statistics Yearbook. Based on the multi-criteria decision analysis (MCDA) algorithm, three different evaluation methods were applied in the study, which are the weighted technique for order preference by similarity to an ideal solution (TOPSIS) method, the weighted rank-sum ratio (RSR) method, and the fuzzy comprehensive evaluation (FCE). Each indicator's weight was calculated by the entropy weight methods objectively. The sensitivity analysis was conducted to validate the stability and accuracy of the rank results. Results The results indicated that the rank values of each year's child health care calculated by the different evaluation methods were not exactly the same, but the overall trend is consistent which is that child health care in China improved year by year from 2000 to 2020. The top 5 were ranked from 2016-2020 and the bottom 5 were ranked from 2000-2004. Conclusions The results indicated that the policies and measures implemented in the medical and health reforms, as well as improved sanitation conditions, availability of healthy food and water, etc., have jointly promoted the development of child health care in China in the past 20 years, providing a scientific theoretical basis for future policy-making to promote child health care.

Clinical Application of Artificial Intelligence in the Ultrasound Classification of Hepatic Cystic Echinococcosis.

Hepatic cystic echinococcosis (HCE) is a zoonotic disease that occurs when the larvae of Echinococcus granulosus parasitize the livers of humans and mammals. HCE has five subtypes, and accurate subtype classification is critical for choosing a treatment strategy. To evaluate the clinical utility of artificial intelligence (AI) based on convolutional neural networks (CNNs) in the classification of HCE subtypes via ultrasound imaging, we collected ultrasound images from 4,012 HCE patients at the First Affiliated Hospital of Xinjiang Medical University between 2008 and 2020. Specifically, 1,820 HCE images from 967 patients were used as the training and validation sets for the construction of the AI model, and the remaining 6,808 images from 3,045 patients were used as the test set to evaluate the performance of the AI models. The 6,808 images were randomly divided into six groups, and each group contained equal proportions of the five subtypes. The data of each group were analyzed by a resident physician. The accuracy of HCE subtype classification by the AI model and by manual inspection was compared. The AI HCE classification model showed good performance in the diagnosis of subtypes CE1, CE2, CE4, and CE5. The overall accuracy of the AI classification (90.4%) was significantly greater than that of manual classification by physicians (86.1%; P <0.05). The CNN can better identify the five subtypes of HCE on ultrasound images and should help doctors with little experience in more accurately diagnosing HCE.

Multiclassification of Hepatic Cystic Echinococcosis by Using Multiple Kernel Learning Framework and Ultrasound Images.

To properly treat and care for hepatic cystic echinococcosis (HCE), it is essential to make an accurate diagnosis before treatment. OBJECTIVE: The objective of this study was to assess the diagnostic accuracy of computer-aided diagnosis techniques in classifying HCE ultrasound images into five subtypes. METHODS: A total of 1820 HCE ultrasound images collected from 967 patients were included in the study. A multi-kernel learning method was developed to learn the texture and depth features of the ultrasound images. Combined kernel functions were built-in Support Vector Machine (MK-SVM) for the classification work. The experimental results were evaluated using five-fold cross-validation. Finally, our approach was compared with three other machine learning algorithms: the decision tree classifier, random forest, and gradient boosting decision tree. RESULTS: Among all the methods used in the study, the MK-SVM achieved the highest accuracy of 96.6% on the fused feature set. CONCLUSION: The multi-kernel learning method effectively learns different image features from ultrasound images by utilizing various kernels. The MK-SVM method, which combines the learning of texture features and depth features separately, has significant application value in HCE classification tasks.

Harvest residue recycling rather than slash-burning results in the enhancement of soil fertility and bacterial community stability in Eucalyptus plantations.

Deforestation and slash combustion have substantial adverse impacts on the atmosphere, soil and microbe. Despite this awareness, numerous individuals persist in opting for high-intensity Eucalyptus planting through slash-burning in pursuit of immediate profits while disregarding the environmental significance and destroying the soil. Slash-unburnt agriculture can effectively safeguard the ecological environment, and compared with slash-burning, there remains a limited understanding of its regulatory mechanisms on soil fertility and microbial community. Also, large uncertainty persists regarding the utilization of harvest residues. Thoroughly investigating these questions from various perspectives encompassing physical soil characteristics, nutrient availability, bacterial community structures, and stability is crucial. To explore the ecological advantages of slash-unburnt techniques on microorganisms and their associated ecosystems, we used two slash-unburnt (Unburnt) planting techniques: Spread (naturally and evenly covering the forest floor after logging) and Stack (residues are piled along contour lines) as well as the traditional slash Burnt method (Burnt) in a Eucalyptus plantation. A comparative analysis was conducted between the two methods. We observed that over a span of 4 years, despite the initial lower application of fertilizer in the Unburnt treatments compared with the Burnt treatment during the first 2 years, the Unburnt treatment gradually caught up or even surpassed and attained similar nutrient levels as the Burnt treatment. Alphaproteobacteria was the main phyla that indicated the difference in soil bacterial communities between Burnt and Unburnt treatments. The microbial networks also highlighted the significance of the Unburnt method, as it contributed to the preservation of crucial network nodes and the stability of soil bacterial communities. Therefore, rational utilization of harvest residue may effectively avoid the vast damage caused by slash-burning to Eucalyptus trees and the soil environment but may also increase the potential for restoring soil fertility, improving fertilizer utilization efficiency, and maintaining microbial community stability over time.

A PRISMA meta-analysis for diagnostic value of microRNA-21 in head and neck squamous cell carcinoma along with bioinformatics research.

OBJECTIVES: The use of miR-21 expression remains vague in diagnosis of head and neck squamous cell carcinoma (HNSCC). This study aimed to systematically evaluate the diagnostic potential of the miR-21 expression in patients with HNSCCs through investigating and summarizing the results reported in the literature. METHODS: Extant medical databases were examined for articles of clinical study assessing the miR-21 expression in HNSCC cases, published in the past 20 years. Bioinformatics research was also performed for finding miR-21 targets differentially expressed in HNSCC so as to present their biological behaviors. RESULTS: Our meta-analysis comprised 11 studies including 622/450 cases in HNSCC/control group. Forest plots displayed miR-21 which possessed significantly good specificity (0.76, p < 0.001) and sensitivity (0.80, p < 0.001). Diagnostic odds ratio was 2.46 (95% CI 1.87-3.24). Positive and negative likelihood ratio was 3.40 (95% CI 1.94-5.97) and 0.26 (95% CI 0.18-0.38), respectively. Area under the receiver operating characteristic curve was 0.85. CONCLUSION: This study is the highest level of evidence presently available in diagnosing HNSCC. This PRISMA meta-analysis indicated that the pooled results were robust, confirming the oncogenic potential of miR-21 that could be used successfully as a screening biomarker in HNSCC patients. Specifically, the overexpression of miR-21 in these patients presents a worse survival outcome.

HCEs-Net: Hepatic cystic echinococcosis classification ensemble model based on tree-structured Parzen estimator and snap-shot approach.

BACKGROUND: Hepatic cystic echinococcosis (HCE) still has a high misdiagnosis rate, and misdiagnosis may lead to wrong treatments seriously harmful for the patients. Precise diagnosis of HCE relies heavily on the experience of clinical experts with auxiliary diagnostic tools using medical images. PURPOSE: This paper intends to improve the diagnostic accuracy for HCE by employing a method which combines deep learning with ensemble method. METHODS: We proposed a method, namely HCEs-Net, for classification of five HCE subtypes using ultrasound images. It takes first the snap-shot strategy to obtain sub-models from the pre-trained VGG19, ResNet18, ViT-Base, and ConvNeXt-T models, then a stacking process to ensemble those sub-models. Afterwards, it uses the tree-structured Pazren estimator (TPE) to optimize the hyperparameters. The experiments were evaluated by the five-fold cross-validation process. RESULTS: A total of 3083 abdominal ultrasound images from 972 patients covering five subtypes of HCE were utilized in this study. The experiments were conducted to predict the HCE subtype, and results of modeling performance evaluation were reported in terms of precision, recall, F1-score, and AUC. The stacking model based on three ConvNeXt-T sub-models showed the best performance, with precision 85.9%, recall 85.5%, F1-score 85.7%, and AUC 0.971 which are higher than the compared state-of-the-art models. CONCLUSION: The stacking model of three ConvNeXt-T sub-models shows comparable or superior performance to the other methods, including VGG19, ResNet18 and ViT-Base. It has the potential to enhance clinical diagnosis for HCE.

Risk assessment of venous thromboembolism in head and neck cancer patients and its establishment of a prediction model.

IMPORTANCE: Venous thromboembolism (VTE) is closely relevant to head and neck cancer (HNC) prognosis, but little data exist on the risk prediction of VTE in patients with HNC. OBJECTIVE: To study the risk factors regarding VTE in HNC patients and construct a nomogram model for its prediction. DESIGN, SETTING, AND PARTICIPANTS: A cross-sectional retrospective study was implemented to comparatively analyze 220 HNC patients from January 2018 to December 2021. The Lasso algorithm was used to optimize the selection of variables. A nomogram model for predicting HNC-associated VTE was established using multivariate logistic regression analysis. Internal validation of the model was performed by bootstrap resampling (1000 times). Calibration plot and decision curve analysis (DCA) were applied to evaluate the calibration capability of the prediction model. MAIN OUTCOME AND MEASURE: The demographics, medical history, blood biochemical indicators, and modalities of treatment were included for analysis. RESULTS: The incidence of HNC-associated VTE was 2.8% (55/1967) in authors' affiliation. Five variables of risk factors, including surgery, radiochemotherapy, D-dimer, aspartate transaminase, and globulin, were screened and selected as predictors by Lasso algorithm. A prediction model that incorporated these independent predictors was developed and presented as the nomogram. The model showed good discrimination with a C-index of 0.972 (95% CI: 0.934-0.997), and had an area under the receiver operating characteristic curve value of 0.981 (p < 0.001, 95% CI: 0.964-0.998). The calibration curve displayed good agreement of the predicted probability with the actual observed probability for HNC-associated VTE. The DCA plot showed that the application of this nomogram was associated with net benefit gains in clinical practice. CONCLUSIONS AND RELEVANCE: The high-performance nomogram model developed in this study may help early diagnose the risk of VTE in HNC patients and to guide individualized decision-making on thromboprophylaxis.

Potential effects of soil chemical and biological properties on wood volume in Eucalyptus urophylla × Eucalyptus grandis hybrid plantations and their responses to different intensity applications of inorganic fertilizer.

Long-term and high-intensity application of inorganic fertilizer leads to a strong variation of soil characteristics. The changes in soil chemical and biological properties can significantly affect the yield of Eucalyptus plantation. However, the mechanism of soil chemical properties affecting wood volume mediated by biological factors is not clear. The purpose of this study was to identify which soil properties were affected by different fertilization intensities and to disentangle the dominant factors affecting Eucalyptus volume. After clear felling evergreen broad-leaved forest, a Eucalyptus plantation was established that was coppiced every 5 years and fertilized every year. Within this plantation, areas with different treatments were established. These treatments were a 5-year growth period (low); two times 5-year growth period (medium); and three times 5-year growth period (high). In each treatment area and in a nearby evergreen broad-leaved forest (EBLF Control), five sample plots per treatment were set up. Various biological and chemistry analyses (18 in total) were related to determining the most important path and index for optimizing Eucalyptus plantation. The analysis of variance of enzyme activity and microbial biomass showed that the soil biological characteristics decreased over 10 years of plantation, and the enzyme activity was close to the state of EBLF control in medium, while the microbial biomass failed to return to its original state during continuous planting. Redundancy analysis results show that there was a strong correlation in chemical indicators and biological characteristics. Partial least square structural equation model showed that total phosphorus, nitrate nitrogen, urease, catalase, and microbial biomass nitrogen and phosphorus were the most influential soil biochemical factors, and the indirect effect of chemical properties on volume was achieved by microorganisms through enzyme activity. Continuous planting and large-scale application of inorganic fertilizer would lead to a decrease in plantation yield and fertilizer utilization efficiency and would affect the microbial biomass and enzyme activity by destroying the stability of soil chemical properties.

Effect of Prognostic Factors of Postoperative Radiotherapy in Oral Squamous Cell Carcinoma: A SEER-Based Study.

Objective: The treatment of oral squamous cell carcinoma (OSCC) is dominated by surgery and radiochemotherapy, but its prognosis is still unsatisfactory, with around five tenths of 5-year survival. This study aimed to assess the prognosis of OSCC patients treated with surgery with and without postoperative radiotherapy. Study Design: Retrospective study. Methods: The clinicopathological information and follow-up datasets on patients with OSCC (T1-4 and/or N+) registered from 2010 to 2015 were downloaded from the Surveillance, Epidemiology, and End Results database. Totally 7231 enrolled subjects were divided into a case group (surgery alone, n = 4167) and a control group (surgery combined with postoperative radiotherapy, n = 3064). One-to-one matching was performed by propensity score matching to make the baseline data comparable between the 2 subgroups. Multivariate Cox regression analysis was used to calculate hazard ratios (HR) of various clinicopathological features. The Kaplan-Meier method and log-rank test were used to plot the survival curves. Results: The majority of patients in case group were tumor stage I (n = 2569, 61.7%), whereas most patients in control group were stages III to IV (n = 2360, 77.1%). In the case group, the 1-, 3-, and 5-year overall survival (OS; 76%, 59.5%, 53.7%) were significantly lower than those of the control group (85.1%, 64.1%, 55.8%; P < .0001). Similarly, the 1-, 3-, and 5-year cancer-specific survival (CSS) of the case group (80.2%, 66.6%, 63.3%) were significantly lower than those of the control group (87.2%, 69.3%, 63.9%, respectively; P < .0001). Cox multivariate analysis indicated that age, differentiation, clinical stage, and tumor-node-metastasis stage affected the prognosis of OSCC patients, while postoperative radiotherapy was a protective factor (OS: HR = 0.649, P < .001; CSS: HR = 0.702, P < .001). Conclusions: Postoperative radiation was an independent protective factor, hence, the combination of surgery plus radiotherapy is more beneficial for the survival of patients with OSCC, particularly for advanced cases.

HPIP promotes thyroid cancer cell growth, migration and EMT through activating PI3K/AKT signaling pathway.

Hematopoietic pre-B cell leukemia transcription factor (PBX)-interacting protein (HPIP), a co-repressor for the transcription factor PBX, is a nucleo-cytoplasmic shuttling protein. Increasing evidence suggests that HPIP is an oncogene which is frequently overexpressed in many human carcinomas. However, the role of HPIP in thyroid carcinoma is still unclear. Therefore, in this study, we investigated the role of HPIP in thyroid carcinoma, and explored the underling mechanism. We found that the expression of HPIP is upregulated in thyroid carcinoma cell lines. Knockdown of HPIP inhibits thyroid carcinoma cell proliferation, migration/invasion and epithelial-mesenchymal transition (EMT). HPIP knockdown also reduces thyroid tumor growth in nude mice. Furthermore, knockdown of HPIP significantly inhibits the expression of phosphorylated PI3K and AKT in thyroid carcinoma cells. Taken together, these results suggest that knockdown of HPIP inhibits the proliferation, migration and EMT by suppressing the PI3K/AKT pathway, and HPIP may be a potential therapeutic target for the treatment of thyroid carcinoma.