MSS-UNet: A Multi-Spatial-Shift MLP-based UNet for skin lesion segmentation.

Multilayer perceptron (MLP) networks have become a popular alternative to convolutional neural networks and transformers because of fewer parameters. However, existing MLP-based models improve performance by increasing model depth, which adds computational complexity when processing local features of images. To meet this challenge, we propose MSS-UNet, a lightweight convolutional neural network (CNN) and MLP model for the automated segmentation of skin lesions from dermoscopic images. Specifically, MSS-UNet first uses the convolutional module to extract local information, which is essential for precisely segmenting the skin lesion. We propose an efficient double-spatial-shift MLP module, named DSS-MLP, which enhances the vanilla MLP by enabling communication between different spatial locations through double spatial shifts. We also propose a module named MSSEA with multiple spatial shifts of different strides and lighter external attention to enlarge the local receptive field and capture the boundary continuity of skin lesions. We extensively evaluated the MSS-UNet on ISIC 2017, 2018, and PH2 skin lesion datasets. On three datasets, the method achieves IoU metrics of 85.01%±0.65, 83.65%±1.05, and 92.71%±1.03, with a parameter size and computational complexity of 0.33M and 15.98G, respectively, outperforming most state-of-the-art methods.The code is publicly available at https://github.com/AirZWH/MSS-UNet.

Anisodamine hydrobromide in the treatment of critically ill patients with septic shock: a multicenter randomized controlled trial.

BACKGROUND: Septic shock is the development of sepsis to refractory circulatory collapse and metabolic derangements, characterized by persistent hypotension and increased lactate levels. Anisodamine hydrobromide (Ani HBr) is a Chinese medicine used to improve blood flow in circulatory disorders. The purpose of this study was to determine the therapeutic efficacy of Ani HBr in the treatment of patients with septic shock. METHODS: This was a prospective, multicenter, randomized controlled trial focusing on patients with septic shock in 16 hospitals in China. Patients were randomly assigned in a 1:1 ratio to either the treatment group or the control group. The primary endpoint was 28-day mortality. The secondary outcomes included 7-day mortality, hospital mortality, hospital length of stay, vasopressor-free days within 7 days, etc. These indicators were measured and collected at 0, 6h, 24h, 48h, 72h and 7d after the diagnosis. RESULTS: Between September 2017 and March 2021, 404 subjects were enrolled. 203 subjects received Ani HBr and 201 subjects were assigned to the control group. The treated group showed lower 28-day mortality than the control group. Stratified analysis further showed significant differences in 28-day mortality between the two groups for patients with a high level of illness severity. We also observed significant differences in 7-day mortality, hospital mortality and some other clinical indicators between the two groups. CONCLUSION: Ani HBr might be an important adjuvant to conventional treatment to reduce 28-day mortality in patients with septic shock. A large-scale prospective randomized multicenter trial is warranted to confirm our results.

Developing a novel necroptosis-related signature to evaluate the prognostic and therapeutic characteristics of esophageal cancer.

BACKGROUND: The prognostic assessment and therapeutic interventions of esophageal cancer (ESCA) require novel molecular targets. The prognostic value of necroptosis, a specific mode of programmed cell death strongly linked to cancer progression, remains largely unexplored in ESCA. The primary goal of this research is to develop a necroptosis-based prognostic signature, which will represent the microenvironmental characteristics and prognosis of individuals diagnosed with ESCA. METHODS: Transcriptome data of ESCA samples from The Cancer Genome Atlas were utilized to screen for necroptosis-related long non-coding RNAs (NR-lncRNAs) and genes (NRGs). The research employed the least absolute shrinkage and selection operator (LASSO) regression and univariate Cox regression analysis to identify prognostic candidates. Based on these analyses, a signature was developed in the training set and subsequently verified in the testing and entire sets. A clinicopathologic relevance assessment was carried out, after which a nomogram was established. The features of the immune microenvironment, functional pathways, mutational burden, checkpoint expression, and stemness of tumors were analyzed. Moreover, the sensitivity of individuals to immunotherapy and chemotherapy was compared for therapeutic guidance. RESULTS: A necroptosis-associated signature comprising two genes and eleven lncRNAs was constructed. High-risk patients showed worse prognosis and clinicopathologic features, with more tumor-infiltrating naïve B cells, CD4+ memory resting T cells, and regulatory T cells. Furthermore, stromal and ESTIMATE scores were decreased along with increased stemness scores and tumor mutational burden in high-risk individuals. For the quantitative prediction of the outcomes of individuals, a nomogram was established. High-risk individuals showed greater sensitivity to immunotherapy while low-risk individuals benefited more from conventional chemotherapeutic or targeted therapy. CONCLUSION: A necroptosis-related prognostic signature was developed to study the tumor microenvironment, mutational burden, clinical features, and the treatment response of ESCA patients. This may contribute to precision medicine for ESCA.

Targeted delivery of Dbait by an artificial extracellular vesicle for improved radiotherapy sensitivity of esophageal cancer.

Intensification of radiotherapy has been shown to be an effective way for improving the therapeutic efficacy of radiation sensitive malignancies such as esophageal cancer (EC). The application of DNA Bait (Dbait), a type of DNA repair inhibitor, is an emerging strategy for radiosensitization. In this study, a Eca-109 cancerous cytomembrane-cloaked biomimetic drug delivery system (DDS), CMEC-Dbait, was designed and successfully fabricated, for targeted delivery of Dbait. Our systematic evaluation demonstrated that the ingenious artificial gastrointestinal extracellular vesicle owns neat spherical structure, proper particle size (154.6±5.5 nm) and surface charge (2.6±0.3 mV), favourable biocompatibility and immunocompatibility, being conducive to in vivo drug delivery. Besides, Eca-109 cytomembrane coating endowed CMEC-Dbait with effective targeting ability to homologous EC cells. Owing to these advantages, the biomimetic DDS was proved to be a potent radiosensitizer in vitro, indicated by remarkably reduced cell viability and enhanced cellular apoptosis by the combination therapy of radiation and CMEC-Dbait. The result was validated in vivo using mouse xenograft models of EC, the results illustrated that radiotherapy plus CMEC-Dbait significantly suppressed tumor growth and prolonged survival of tumor bearing mice. Western blotting results showed that CMEC-Dbait can significantly inhibit DNA damage repair signaling pathways by simulating DNA double-strand breaks both in and ex vivo. In conclusion, the versatile biomimetic CMEC-Dbait was characterized of low toxicity, excellent biocompatibility and satisfactory drug delivery efficiency, which is confirmed to be an ideal radiosensitizer for homologous cancer and merits further investigation in both pre-clinical and clinical studies.

Semi-supervised medical image segmentation via cross-guidance and feature-level consistency dual regularization schemes.

BACKGROUND: Semi-supervised learning is becoming an effective solution for medical image segmentation because of the lack of a large amount of labeled data. PURPOSE: Consistency-based strategy is widely used in semi-supervised learning. However, it is still a challenging problem because of the coupling of CNN-based isomorphic models. In this study, we propose a new semi-supervised medical image segmentation network (DRS-Net) based on a dual-regularization scheme to address this challenge. METHODS: The proposed model consists of a CNN and a multidecoder hybrid Transformer, which adopts two regularization schemes to extract more generalized representations for unlabeled data. Considering the difference in learning paradigm, we introduce the cross-guidance between CNN and hybrid Transformer, which uses the pseudo label output from one model to supervise the other model better to excavate valid representations from unlabeled data. In addition, we use feature-level consistency regularization to effectively improve the feature extraction performance. We apply different perturbations to the feature maps output from the hybrid Transformer encoder and keep an invariance of the predictions to enhance the encoder's representations. RESULTS: We have extensively evaluated our approach on three typical medical image datasets, including CT slices from Spleen, MRI slices from the Heart, and FM Nuclei. We compare DRS-Net with state-of-the-art methods, and experiment results show that DRS-Net performs better on the Spleen dataset, where the dice similarity coefficient increased by about 3.5%. The experimental results on the Heart and Nuclei datasets show that DRS-Net also improves the segmentation effect of the two datasets. CONCLUSIONS: The proposed DRS-Net enhances the segmentation performance of the datasets with three different medical modalities, where the dual-regularization scheme extracts more generalized representations and solves the overfitting problem.

Dual encoder network with transformer-CNN for multi-organ segmentation.

Medical image segmentation is a critical step in many imaging applications. Automatic segmentation has gained extensive concern using a convolutional neural network (CNN). However, the traditional CNN-based methods fail to extract global and long-range contextual information due to local convolution operation. Transformer overcomes the limitation of CNN-based models. Inspired by the success of transformers in computer vision (CV), many researchers focus on designing the transformer-based U-shaped method in medical image segmentation. The transformer-based approach cannot effectively capture the fine-grained details. This paper proposes a dual encoder network with transformer-CNN for multi-organ segmentation. The new segmentation framework takes full advantage of CNN and transformer to enhance the segmentation accuracy. The Swin-transformer encoder extracts global information, and the CNN encoder captures local information. We introduce fusion modules to fuse convolutional features and the sequence of features from the transformer. Feature fusion is concatenated through the skip connection to smooth the decision boundary effectively. We extensively evaluate our method on the synapse multi-organ CT dataset and the automated cardiac diagnosis challenge (ACDC) dataset. The results demonstrate that the proposed method achieves Dice similarity coefficient (DSC) metrics of 80.68% and 91.12% on the synapse multi-organ CT and ACDC datasets, respectively. We perform the ablation studies on the ACDC dataset, demonstrating the effectiveness of critical components of our method. Our results match the ground-truth boundary more consistently than the existing models. Our approach gains more accurate results on challenging 2D images for multi-organ segmentation. Compared with the state-of-the-art methods, our proposed method achieves superior performance in multi-organ segmentation tasks. Graphical Abstract The key process in medical image segmentation.

LncRNA-CASC15 knockdown inhibits the progression of esophageal squamous cell carcinoma through targeting miR-33a-5p/PTGS2 axis.

LncRNA CASC15 has been determined as a novel tumor-related lncRNA in many cancers. However, the in-detail role of CASC15 remains elusive in esophageal squamous cell carcinoma (ESCC). CASC15 expression level was detected in 113 ESCC tissues and paired adjacent normal tissues and in human ESCC cell lines. The effects of CASC15 on ESCC proliferation, migration, and invasion were assessed using CCK-8 and transwell assays. In addition, the potential downstream molecules of CASC15 were searched and confirmed by software algorithms, RT-qPCR, western blot, dual-luciferase reporter, and rescue experiments. CASC15 was upregulated in ESCC tissues and cell lines. CASC15 overexpression was associated with poorer prognosis in ESCC patients. Functionally, CASC15 knockdown inhibited cell proliferation, migration, and invasion of ESCC cells. Mechanistically, it was confirmed that CASC15 acts as competing endogenous RNA for miR-33a-5p to regulate PTGS2 expression. In addition, rescue assay showed that miR-33a-5p knockdown or PTGS2 overexpression abolished the cell proliferation, migration, and invasion inhibition role of CASC15 knockdown. In conclusion, this study indicates that CASC15 was upregulated in ESCC and CASC15 knockdown hindered ESCC progression through targeting the miR-33a-5p/PTGS2 axis. CASC15 might serve as a novel biomarker and therapeutic target for ESCC.

TDD-UNet:Transformer with double decoder UNet for COVID-19 lesions segmentation.

The outbreak of new coronary pneumonia has brought severe health risks to the world. Detection of COVID-19 based on the UNet network has attracted widespread attention in medical image segmentation. However, the traditional UNet model is challenging to capture the long-range dependence of the image due to the limitations of the convolution kernel with a fixed receptive field. The Transformer Encoder overcomes the long-range dependence problem. However, the Transformer-based segmentation approach cannot effectively capture the fine-grained details. We propose a transformer with a double decoder UNet for COVID-19 lesions segmentation to address this challenge, TDD-UNet. We introduce the multi-head self-attention of the Transformer to the UNet encoding layer to extract global context information. The dual decoder structure is used to improve the result of foreground segmentation by predicting the background and applying deep supervision. We performed quantitative analysis and comparison for our proposed method on four public datasets with different modalities, including CT and CXR, to demonstrate its effectiveness and generality in segmenting COVID-19 lesions. We also performed ablation studies on the COVID-19-CT-505 dataset to verify the effectiveness of the key components of our proposed model. The proposed TDD-UNet also achieves higher Dice and Jaccard mean scores and the lowest standard deviation compared to competitors. Our proposed method achieves better segmentation results than other state-of-the-art methods.

A regularization-driven Mean Teacher model based on semi-supervised learning for medical image segmentation.

Objective.A semi-supervised learning method is an essential tool for applying medical image segmentation. However, the existing semi-supervised learning methods rely heavily on the limited labeled data. The generalization performance of image segmentation is improved to reduce the need for the number of labeled samples and the difficulty of parameter tuning by extending the consistency regularization.Approach.We propose a new regularization-driven Mean Teacher model based on semi-supervised learning for medical image segmentation in this work. We introduce a regularization-driven strategy with virtual adversarial training to improve segmentation performance and the robustness of the Mean Teacher model. We optimize the unsupervised loss function and the regularization term with an entropy minimum to smooth the decision boundary.Main results.We extensively evaluate the proposed method on the International Skin Imaging Cooperation 2017(ISIC2017) and COVID-19 CT segmentation datasets. Our proposed approach gains more accurate results on challenging 2D images for semi-supervised medical image segmentation. Compared with the state-of-the-art methods, the proposed approach has significantly improved and is superior to other semi-supervised segmentation methods.Significance.The proposed approach can be extended to other medical segmentation tasks and can reduce the burden of physicians to some extent.

The presence of lepidic and micropapillary/solid pathological patterns as minor components has prognostic value in patients with intermediate-grade invasive lung adenocarcinoma.

BACKGROUND: The acinar- and papillary-predominant histological subtypes are the most common types of invasive lung adenocarcinoma and are considered "intermediate-grade" carcinomas with heterogeneous prognosis. This study investigated the prognostic significance of the lepidic and micropapillary/solid pathological patterns as minor components in patients with intermediate-grade lung adenocarcinomas. METHODS: A total of 697 patients with pathological N0M0 acinar/papillary-predominant lung adenocarcinomas ≤3 cm in diameter, who underwent curative resection in our institution between June 1, 2014 and August 31, 2016, were retrospectively enrolled in this study. Acinar/papillary-predominant lung adenocarcinomas were classified into four subtypes according to the presence of the minor pathological components lepidic (Lep), micropapillary (MP), and solid (S). The subtypes were MP/S-Lep+, MP/S-Lep-, MP/S+Lep+, and MP/S+Lep-. The 5-year recurrence-free survival (RFS) and overall survival (OS) were recorded. Factors affecting survival were analyzed by Cox regression method. RESULTS: Among 697 intermediate-grade lung adenocarcinomas, the distribution of patients was as follows: MP/S-Lep+ type (n=314; 45.0%), MP/S-Lep- type (n=144; 20.7%), MP/S+Lep+ type (n=133; 19.1%), and MP/S+Lep- type (n=106; 15.2%). The 5-year RFS rates were 98.7%, 94.4%, 94.0%, and 81.9%, respectively (P<0.001). The 5-year OS rates were 98.4%, 94.4%, 96.6%, and 87.7%, respectively (P<0.001). Multivariate analysis revealed that the MP/S+Lep- subtype was an independent poor prognostic factor of both RFS and OS. CONCLUSIONS: Acinar/papillary-predominant adenocarcinoma is an "intermediate-grade" carcinoma that can be further classified into subtypes according to the presence of lepidic and micropapillary/solid pathological patterns with significantly different prognosis. This classification may be useful in evaluating the recurrence risk and guiding adjuvant therapies in patients with acinar/papillary-predominant stage I lung adenocarcinoma.

Flexible thermochromic fabrics enabling dynamic colored display.

Color-changeable fibers can provide diverse functions for intelligent wearable devices such as novel information displays and human-machine interfaces when woven into fabric. This work develops a low-cost, effective, and scalable strategy to produce thermochromic fibers by wet spinning. Through a combination of different thermochromic microcapsules, flexible fibers with abundant and reversible color changes are obtained. These color changes can be clearly observed by the naked eye. It is also found that the fibers exhibit excellent color-changing stability even after 8000 thermal cycles. Moreover, the thermochromic fibers can be fabricated on a large scale and easily woven or implanted into various fabrics with good mechanical performance. Driven by their good mechanical and physical characteristics, applications of thermochromic fibers in dynamic colored display are demonstrated. Dynamic quick response (QR) code display and recognition are successfully realized with thermochromic fabrics. This work well confirms the potential applications of thermochromic fibers in smart textiles, wearable devices, flexible displays, and human-machine interfaces.

The Effect of Plasma Triglyceride-Lowering Therapy on the Evolution of Organ Function in Early Hypertriglyceridemia-Induced Acute Pancreatitis Patients With Worrisome Features (PERFORM Study): Rationale and Design of a Multicenter, Prospective, Observational, Cohort Study.

Background: Acute pancreatitis (AP) is a potentially life-threatening inflammatory disease with multiple etiologies. The prevalence of hypertriglyceridemia-induced acute pancreatitis (HTG-AP) has been increasing in recent years. It is reported that early triglyceride (TG) levels were associated with the severity of the disease, and TG- lowering therapies, including medical treatment and blood purification, may impact the clinical outcomes. However, there is no consensus regarding the optimal TG-lowering therapy, and clinical practice varies greatly among different centers. Our objective is to evaluate the TG-lowering effects of different therapies and their impact on clinical outcomes in HTG-AP patients with worrisome features. Methods: This is a multicenter, observational, prospective cohort study. A total of approximately 300 patients with HTG-AP with worrisome features are planned to be enrolled. The primary objective of the study is to evaluate the relationship between TG decline and the evolution of organ failure, and patients will be dichotomized depending on the rate of TG decline. The primary outcome is organ failure (OF) free days to 14 days after enrollment. Secondary outcomes include new-onset organ failure, new-onset multiple-organ failure (MOF), new-onset persistent organ failure (POF), new receipt of organ support, requirement of ICU admission, ICU free days to day 14, hospital free days to day 14, 60-day mortality, AP severity grade (Based on the Revised Atlanta Classification), and incidence of systemic and local complications. Generalized linear model (GLM), Fine and Gray competing risk regression, and propensity score matching will be used for statistical analysis. Discussion: Results of this study will reveal the current practice of TG-lowering therapy in HTG-AP and provide necessary data for future trials.

Faradaic junction and isoenergetic charge transfer mechanism on semiconductor/semiconductor interfaces.

Energy band alignment theory has been widely used to understand interface charge transfer in semiconductor/semiconductor heterojunctions for solar conversion or storage, such as quantum-dot sensitized solar cells, perovskite solar cells and photo(electro)catalysis. However, abnormally high open-circuit voltage and charge separation efficiency in these applications cannot be explained by the classic theory. Here, we demonstrate a Faradaic junction theory with isoenergetic charge transfer at semiconductor/semiconductor interface. Such Faradaic junction involves coupled electron and ion transfer, which is substantively different from the classic band alignment theory only involving electron transfer. The Faradaic junction theory can be used to explain these abnormal results in previous studies. Moreover, the characteristic of zero energy loss of charge transfer in a Faradaic junction also can provide a possibility to design a solar conversion device with a large open-circuit voltage beyond the Shockley-Queisser limit by the band alignment theory.

The Impact of Normal Saline or Balanced Crystalloid on Plasma Chloride Concentration and Acute Kidney Injury in Patients With Predicted Severe Acute Pancreatitis: Protocol of a Phase II, Multicenter, Stepped-Wedge, Cluster-Randomized, Controlled Trial.

Introduction/aim: The supraphysiologic chloride concentration of normal saline may contribute to acute kidney injury (AKI). Balanced crystalloids can decrease chloride concentration and AKI in critically ill patients. We aim to test the hypothesis that, in patients with predicted severe acute pancreatitis (pSAP), compared with saline, fluid therapy with balanced crystalloids will decrease plasma chloride concentration. Methods/Design: This is a multicenter, stepped-wedge, cluster-randomized, controlled trial. All eligible patients presenting to the 11 participating sites across China during the study period will be recruited. All sites will use saline for the first month and sequentially change to balanced crystalloids at the pre-determined and randomly allocated time point. The primary endpoint is the plasma chloride concentration on day 3 of enrollment. Secondary endpoints will include major adverse kidney events on hospital discharge or day 30 (MAKE 30) and free and alive days to day 30 for intensive care admission, invasive ventilation, vasopressors, and renal replacement therapy. Additional endpoints include daily serum chloride and sequential organ failure assessment (SOFA) score over the first seven days of enrollment. Discussion: This study will provide data to define the impact of normal saline vs. balanced crystalloids on plasma chloride concentration and clinical outcomes in pSAP patients. It will also provide the necessary data to power future large-scale randomized trials relating to fluid therapy. Ethics and Dissemination: This study was approved by the ethics committee of Jinling Hospital, Nanjing University (2020NZKY-015-01) and all the participating sites. The results of this trial will be disseminated in peer-reviewed journals and at scientific conferences. Trial registration: The trial has been registered at the Chinese Clinical Trials Registry (ChiCTR2100044432).

Effect of Guo Qing Yi Tang combined with Western medicine cluster therapy on acute pancreatitis.

BACKGROUND: This study evaluated the effect of Guo Qing Yi Tang (GQYT) combined with Western medicine cluster therapy on acute pancreatitis (AP). METHODS: A total of 138 AP patients were recruited and divided into the observation group (68 patients) and control group (70 patients). The control group was treated with cluster therapy alone, while the observation group was treated with trans-jejunum feeding of GQYT combined with cluster therapy. Blood samples were taken before the treatment and 24 h, 72 h, and 1 week after the treatment. The serum concentrations of Di amine oxidase(DAO), Endotoxin(ET), D-lactic acid, Intestinal trefoil factor(ITF), MFG-E8, TNF-α, IL-1ß, IL-6, and IL-8 were determined by using spectrophotometry and enzyme-linked immunosorbent assay. The concentrations of urinary lactulose and mannitol (L/M) were determined by high-performance liquid chromatography, and the urinary L/M value was calculated. RESULTS: Compared with the control group, the observation group had shorter hospital stay, faster recovery, significantly lower APACHE II score, and higher complete response rate (94.12%) after 1 week of treatment (P < 0.05). Moreover, the indicators related to intestinal mucosal barrier function (DAO, MFG-8, L/M) and inflammatory cytokines (TNF-α, IL-6, IL-8) were significantly reduced in the observation group after 1 week of treatment (P < 0.05). CONCLUSION: GQYT combined with cluster therapy for the treatment of AP has definite curative effect and rapid onset, reduces the level of inflammatory factors, and improves intestinal mucosal barrier function and APACHE II score. Thus, it has obvious clinical therapeutic advantages and can be used as a new therapeutic regimen for AP.

MicroRNA-127-5p attenuates severe pneumonia via tumor necrosis factor receptor-associated factor 1.

Pneumonia is a persistent and pervasive disease, the effects of which can be severe. MicroRNA (miR)-127-5p has been utilized as a novel biomarker for the diagnosis of severe pneumonia. The present study aimed to investigate the function of miR-127-5p during severe pneumonia. An in vitro model of severe pneumonia in Ana-1 murine macrophages was established using lipopolysaccharide (LPS). Subsequently, reverse transcription-quantitative PCR and ELISA were performed to detect the mRNA and protein expression levels of interleukin (IL)-1ß, IL-6 and tumor necrosis factor (TNF)-α. Western blotting was also performed to measure the activity of AKT and NF-κB. The results indicated that compared with the control group, LPS treatment increased TNF receptor-associated factor 1 (TRAF1) expression levels and reduced miR-127-5p expression levels. Furthermore, the results revealed that the 3'-untranslated region of TRAF1 was targeted by miR-127-5p. miR-127-5p mimic reduced LPS-induced increases in IL-1ß, IL-6 and TNF-α expression by targeting TRAF1, which was potentially mediated by inactivation of the AKT and NF-κB signaling pathways. Collectively, the results demonstrated that miR-127-5p may attenuate severe pneumonia by reducing LPS-induced inflammatory cytokine production, and inactivating the AKT and NF-κB signaling pathways by targeting TRAF1.

Multicenter Study of Tetanus Patients in Fujian Province of China: A Retrospective Review of 95 Cases.

BACKGROUND: Tetanus is a life-threatening disease in developing countries and is accompanied by a high mortality rate. Although China is the world's largest developing country, there have been few clinical studies on tetanus in China. The purpose of this study was to investigate the epidemiology, incidence, and management of tetanus in Fujian Province and to understand the current treatment and prognosis of tetanus patients. METHODS: This was a retrospective, multicenter observational study of patients who presented with a clinical diagnosis of tetanus at 5 general hospitals in Fujian from January 2008 to December 2018. Data were analyzed using a computer software system. RESULTS: A total of 95 patients were recruited, including 6 newborns. The average age of the adult tetanus patients was 55.53 ± 15.39 years old. None of the patients knew their previous history of tetanus immunization. The rate of having received human tetanus immunoglobulin (HTIG) was 9.47%. A total of 73 (76.84%) patients were cured, 17 (17.89%) patients had an unknown prognosis, and 5 (5.26%) patients died. Age, severity of illness, and complications all increased the total duration of hospitalization. Compared with endotracheal intubation, tracheotomy increased the length of stay in the ICU (Intensive Care Unit) but did not affect the total hospital length of stay for mechanical ventilation. CONCLUSIONS: With the promotion of nationwide immunization against tetanus and the development of critical care medicine, morbidity and mortality rates of tetanus in Fujian are low. It is important to increase awareness among local physicians and staff in charge of tetanus immunization programs and with regard to neonatal tetanus and drug-induced tetanus. The prevention and treatment of tetanus in developing countries should arouse widespread concern in society.

Metallothionein 1M (MT1M) inhibits lung adenocarcinoma cell viability, migration, and expression of cell mobility-related proteins through MDM2/p53/MT1M signaling.

BACKGROUND: Metallothionein 1M (MT1M) functions to regulate cell proliferation and cancer metastasis. This study assessed the effects of MT1M overexpression and mouse double minute 2 homolog (MDM2) knockdown on the regulation of non-small cell lung cancer A549 cell viability, migration, and protein expression in vitro and explored the underlying molecular events. METHODS: A549 cells were stably infected with lentivirus carrying MT1M cDNA or transiently transfected MDM2 siRNA and/or treated with the p53 inhibitor for the assessment of changes in cell viability, wound healing, Transwell migration, and qRT-PCR and Western blot assays. Luciferase reporter assay was performed to investigate p53 binding to the MT1M promoter. RESULTS: The data showed that MT1M overexpression inhibited A549 cell viability and migration capacity in vitro, whereas the p53 inhibitor reversed the inhibition of A549 cell viability and migration caused by MT1M overexpression as well as the expression of MMP2, MMP9, and MMP14. Furthermore, knockdown of MDM2, an upstream inhibitor of p53 activity, was able to reduce A549 cell viability, migration, and protein expression. Thus, MDM2 knockdown had synergistic effects with MT1M overexpression on the suppression of A549 cell viability, migration, and protein expression. CONCLUSIONS: In conclusion, MDM2 can bind to and phosphorylate p53 protein to inactivate the protein, thereby reducing MT1M expression and leading to tumor cell proliferation and migration.

Downregulation of microRNA-370 in esophageal squamous-cell carcinoma is associated with cancer progression and promotes cancer cell proliferation via upregulating PIN1.

PIN1 is a peptidyl-prolyl cis/trans isomerase (PPIase) that controls cell fate by regulating multiple signal transduction pathways and is found to be overexpressed in a variety of malignant tumors. Herein, we found the expression of PIN1 is up-regulated while miRNA-370 (miR-370) down-regulated in both esophageal squamous-cell carcinoma (ESCC) tissues and cells. Transfection of miR-370 can significantly decrease PIN1 expression in targeting ESCC cells. Overexpression of miR-370 can induce decreased cell proliferation and cell cycle arrest, as well as increased apoptosis in ESCC cells, while this function can be significantly prevented by co-transfection of PIN1. Further experimental results demonstrated that ß-catenin, cyclin D1, and caspase activation might be involved in miR-370/PIN1 induced growth inhibition and apoptosis. Besides, low miR-370 and high PIN1 expression significantly correlated with tumor diameter, poor differentiation, tumor invasion and lymph node metastasis in patients diagnosed with ESCC. In conclusion, downregulation of miR-370 in ESCC is associated with cancer progression and promotes cancer cell proliferation via upregulating PIN1, which might be a potential therapeutic target and adverse prognostic factor in the clinic.

Association between vitamin D receptor BsmI polymorphism and bone mineral density in pediatric patients: A meta-analysis and systematic review of observational studies.

BACKGROUND: Vitamin D and the vitamin D receptor (VDR) are important in the metabolic processes that affect bone mineral density (BMD). However, the effect of VDR BsmI polymorphism on BMD in pediatric patients is still unclear. METHODS: Eligible studies were identified from the following electronic databases: PubMed, Embase, the Cochrane Library, and the Chinese CNKI and Wanfang databases before October 1, 2016. Data were extracted from the eligible studies, and associations between VDR BsmI polymorphism and BMD in pediatric patients were estimated with weighted mean differences (WMDs) and 95% confidence intervals (CIs). Subgroup analysis of ethnicity and sensitivity analyses were used to identify sources of heterogeneity. RESULTS: A significant difference was observed between VDR BsmI polymorphism and pediatric BMD levels of the lumbar spine (LS) in the corecessive model (bb vs BB + Bb: WMD = -0.23, 95% CI [-0.35, -0.11], P < 0.01). No significant relationship was found in the dominant, recessive, or codominant models for LS BMD (BB vs Bb: WMD = -0.56, 95% CI [-1.58, 0.46], P = 0.29; BB vs bb: WMD = -0.54, 95% CI [-1.49, 0.41], P = 0.27; and BB vs Bb + bb: WMD = -0.45, 95% CI [-1.71, 0.26], P = 0.22). In addition, we found no remarkable association between the BsmI polymorphism and BMD levels of the femoral neck (FN) in children (BB vs Bb: WMD = -1.08, 95% CI [-3.13, 0.96], P = 0.30; BB vs bb: WMD = 0.98, 95% CI [-0.89, 2.85], P = 0.31; BB vs Bb + bb: WMD = -0.061, 95% CI [-0.30, 0.17], P = 0.61; and bb vs BB + Bb: WMD = 0.82, 95% CI [-0.59, 2.32], P = 0.25). CONCLUSION: Our meta-analysis found that the VDR BsmI genetic polymorphism was correlated with LS BMD level in pediatric patients: compared with those with the B allele, children with the bb genotype were less likely to have lower BMD levels. No significant difference was identified in the pediatric FN BMD levels.