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Osteoarthritis is one of the most prevalent diseases in the world, which affects a wide range of age groups, ranging from children to the elderly. More than 300 million people worldwide suffer from osteoarthritis, which may cause pain, stiffness, tenderness, loss of flexibility, grating sensation, bone spurs and swelling, and other diseases. Medication, surgery, and therapy are the main treatments. For medication, there are Analgesics and Nonsteroidal anti-inflammatory drugs, which have the function of reducing pain and inflammation. Nonsteroidal anti-inflammatory drugs can also reduce pain. For surgery, there are arthroplasty, arthrodesis, and osteotomy. In addition, there are physical therapy and occupational therapy. Those different kinds of therapies have their own advantages. Recent studies have shown that mesenchymal stem cells (MSCS) can be used to treat osteoarthritis, which has the properties of differentiating into chondrocytes and having anti-inflammatory and immunomodulatory effects. These cells are ideal for treating osteoarthritis that requires anti-inflammatory and cartilage replacement. This paper provides a brief overview of the different treatment approaches and aims to compare the pros and cons of each approach.

The multicenter study aimed to explore the relationship between the growth pattern of liver metastases on preoperative MRI and early recurrence in patients with colorectal cancer liver metastases (CRCLM) after surgery.A total of 348 CRCLM patients from 3 independent centers were enrolled, including 130 patients with 339 liver metastases in the primary cohort and 218 patients in validation cohorts. Referring to the gross classification of hepatocellular carcinoma (HCC), the growth pattern of each liver metastasis on MRI was classified into four types: rough, smooth, focal extranodular protuberant (FEP), and nodular confluent (NC). Disease-free survival (DFS) curve was constructed using the Kaplan-Meier method.In primary cohort, 42 (12.4%) of the 339 liver metastases were rough type, 237 (69.9%) were smooth type, 29 (8.6%) were FEP type, and 31 (9.1%) were NC type. Those patients with FEP- and/or NC-type liver metastases had shorter DFS than those without such metastases (p0.05). However, there were no significant differences in DFS between patients with rough- and smooth-type liver metastases and those without such metastases. The patients with FEP- and/or NC-type liver metastases also had shorter DFS than those without such metastases in two external validation cohorts. In addition, 40.5% of high-risk-type (FEP and NC) liver metastases converted to low-risk types (rough and smooth) after neoadjuvant chemotherapy.The FEP- and NC-type liver metastases were associated with early recurrence, which may facilitate the clinical treatment of CRCLM patients.• In the primary cohort, patients with FEP- and NC-type metastases had shorter disease-free survival (DFS) and a higher intrahepatic recurrence rate than patients without such metastases in the liver. • In the primary cohort, there were no significant differences in DFS or intrahepatic recurrence rate between patients with rough- and smooth-type metastases and those without such metastases in the liver. • High-risk patients had shorter DFS and a higher intrahepatic recurrence rate than low-risk patients in primary and external validation cohorts.

The identification of high recurrence risk stage II colon cancer patients was critical to adjuvant chemotherapy decision. However, current definition of high-risk features remains inadequate. This study aimed to construct a model for predicting recurrence risk based on tumor enhancement ratio (TER) on abdominal contrast-enhanced CT scan.282 stage II colon cancer patients were included and randomly divided into training and validation sets in the ratio of 7:3. TER was calculated using maximum tumor attenuation value in contrast-enhanced CT scan divided by the minimum. Kaplan-Meier survival analyses were adopted to evaluate the prognostic value of variables. A model based on TER was built to predict recurrence risk through the LASSO Cox model. The recurrence risk score of patients was calculated based on this model.The optimal cut-off value of TER was 1.83 derived from the time-dependent ROC (tdROC) curve. Patients with high-TER showed increasingly poorer disease-free survival (DFS) in both training (p 0.001) and validation (p 0.001) sets. A model was built based on TER demonstrated satisfactory performance to recurrence risk prediction (C-index: 0.784 in the training set and 0.725 in the validation set). Patients were regrouped into modified high-risk and non-high risk according to recurrence risk score (cut-off value: 1.75) and a significant DFS difference was observed (training set: p 0.001; validation set: p 0.001).TER can serve as a high-risk feature of stage II colon cancer. And a model based on TER provided a new approach to assess recurrence risk of stage II disease.

Wearable sensors demand flexible and concealable devices that can be seamlessly integrated with apparels and clothes. E-textile sensors and devices, built from specially functionalized fibers and yarns and constructed with embroidery and woven processes, provide an ideal solution for different wearable applications. In this article, we propose a textile-based, embroidered passive strain and displacement sensor functioned as a UHF RFID antenna that can be aesthetically integrated with garment fabrics. The antenna structure consists of a dipole arm and a coupling loop mounted with an RFID chip. The displacement between the loop and dipole arm will alter the impedance of the antenna and consequently modulate the backscattered signals from the RFID chip to the reader. The sensor is passive, i.e., no battery is needed on the sensor and the sensing information can be wirelessly retrieved by the reader from a few meters away. The structure is sensitive to strains and displacement caused by body movement. Our experiments demonstrate different applications for this sensor, i.e., when the sensor is embroidered on different locations on human body, such as breast, knees, and elbows, it can be used as a respiration monitor, gesture indicator, etc. to conveniently track and log various forms of body movements.

We have optimised a reverse transcription-loop-mediated isothermal amplification (RT-LAMP) assay for the detection of SARS-CoV-2 from extracted RNA for clinical application. We improved the stability and reliability of the RT-LAMP assay by the addition of a temperature-dependent switch oligonucleotide to reduce self- or off-target amplification. We then developed freeze-dried master mix for single step RT-LAMP reaction, simplifying the operation for end users and improving long-term storage and transportation. The assay can detect as low as 13 copies of SARS-CoV2 RNA per reaction (25-μL). Cross reactivity with other human coronaviruses was not observed. We have applied the new RT-LAMP assay for testing clinical extracted RNA samples extracted from swabs of 72 patients in the UK and 126 samples from Greece and demonstrated the overall sensitivity of 90.2% (95% CI 83.8–94.7%) and specificity of 92.4% (95% CI 83.2–97.5%). Among 115 positive samples which Ct values were less than 34, the RT-LAMP assay was able to detect 110 of them with 95.6% sensitivity. The specificity was 100% when RNA elution used RNase-free water. The outcome of RT-LAMP can be reported by both colorimetric detection and quantifiable fluorescent reading. Objective measures with a digitized reading data flow would allow for the sharing of results for local or national surveillance.

As people continue to pay attention to environmental issues, the concept of green consumption has emerged. In order to study the effects of the guidance information on green consumption behavior, this paper chose two common situations in social life: “household electricity-saving” and “carton recycling,” and designed an inter-group experiment of 2 (Message Framing: Gain framing/Loss framing) × 2 (Language Intensity: Assertive language/Nonassertive language) × 2 (Self-construction: Interdependent self-construal/Independent self-construal), based on the Self-construal Theory. It aimed to examine the influence of different message strategies on the green consumption behavior willingness of information receivers. It was found that for interdependent individuals, the gain framing message has more positive influence on the intention of green consumption behavior, while the loss framing can better promote independent individuals’ willingness. Nonassertive message had a positive impact on the intention of green consumption behavior of both types of individuals. Besides, when the message is nonassertive, gaining framing and losing framing message has a more significant role in promoting the green consumption behavior willingness of interdependent individuals and independent individuals, respectively.

Verrucous epidermal nevus (VEN) is a benign skin disease that seriously affects appearance. Numerous therapeutic methods have been tried with varying results. However, there are few reports on the treatment of VEN by photodynamic therapy (PDT). This study aimed to evaluate the efficacy and adverse effects of 5-aminolevulinic acid (ALA)-PDT in VEN treatment with a long-term follow-up. A total of 16 patients with VEN received ALA-PDT and were followed up for more than 1 year to observe the treatment effects, adverse reactions, and patients' satisfaction. Complete improvement of lesions was observed in 11 patients (three to six sessions of ALA-PDT). Two patients obtained 90-99% improvement (five sessions) and 50-89% improvement in three patients (three to six sessions). They were satisfied with the treatment effects, with an average satisfaction of 4.19/5 (±0.91). Long-term follow-up ranging 14-50 months showed a low recurrence rate (2/16) and no scar left after ALA-PDT. The results demonstrate that ALA-PDT is an effective and safe therapy in treating VEN with mild adverse reactions and a low risk of scar formation.

Background The prognosis for patients with colorectal-cancer liver metastases (CRLM) after curative surgery remains poor and shows great heterogeneity. Early recurrence, defined as tumor recurrence within 6 months of curative surgery, is associated with poor survival, requiring earlier detection and intervention. This study aimed to develop and validate a bedside model based on clinical parameters to predict early recurrence in CRLM patients and provide insight into post-operative surveillance strategies. Material and methods A total of 202 consecutive CRLM patients undergoing curative surgeries between 2012 and 2019 were retrospectively enrolled and randomly assigned to the training (n = 150) and validation (n = 52) sets. Baseline information and radiological, pathological, and laboratory findings were extracted from medical records. Predictive factors for early recurrence were identified via a multivariate logistic-regression model to develop a predictive nomogram, which was validated for discrimination, calibration, and clinical application. Results Liver-metastases number, lymph-node suspicion, neurovascular invasion, colon/rectum location, albumin and post-operative carcinoembryonic antigen, and carbohydrate antigen 19–9 levels (CA19–9) were independent predictive factors and were used to construct the nomogram for early recurrence after curative surgery. The area under the curve was 0.866 and 0.792 for internal and external validation, respectively. The model significantly outperformed the clinical risk score and Beppu’s model in our data set. In the lift curve, the nomogram boosted the detection rate in post-operative surveillance by two-fold in the top 30% high-risk patients. Conclusion Our model for early recurrence in CRLM patients after curative surgeries showed superior performance and could aid in the decision-making for selective follow-up strategies.

Background Bilateral herpes zoster (BHZ) is an atypical presentation of herpes zoster (HZ), with few cases reported before. Ramsay Hunt syndrome (RHS) is an uncommon complication of VZV infection. Cases of BHZ with RHS in immunocompetent adults have been reported rarely. Case presentation We described an immunocompetent adult who suffered from left-sided thoracic herpes zoster and contralateral RHS simultaneously, and summarizes the characteristics of BHZ. Conclusions Cases of BHZ with RHS in immunocompetent adults have not been reported previously. Antivirus - glucocorticoid combination therapy showed a good effect in this case.

Cisplatin-based chemotherapy remains the primary treatment for unresectable and metastatic muscle-invasive bladder cancers (MIBCs). However, tumors frequently develop chemoresistance. Here, we established a primary and orthotopic MIBC mouse model with gene-edited organoids to recapitulate the full course of chemotherapy in patients. We found that partial squamous differentiation, called semi-squamatization, is associated with acquired chemoresistance in both mice and human MIBCs. Multi-omics analyses showed that cathepsin H (CTSH) is correlated with chemoresistance and semi-squamatization. Cathepsin inhibition by E64 treatment induces full squamous differentiation and pyroptosis, and thus specifically restrains chemoresistant MIBCs. Mechanistically, E64 treatment activates the tumor necrosis factor pathway, which is required for the terminal differentiation and pyroptosis of chemoresistant MIBC cells. Our study revealed that semi-squamatization is a type of lineage plasticity associated with chemoresistance, suggesting that differentiation via targeting of CTSH is a potential therapeutic strategy for the treatment of chemoresistant MIBCs.

The effect of Auriculariacornea (AC) as an alternative for pork fat on the physico-chemical properties and sensory characteristics of cooked sausage were evaluated. The results indicated that replacement of pork fat with AC led to a significant increase in the protein, ash, moisture, cooking loss, water holding capacity, springiness, and chewiness, especially isoleucine, leucine, proline, palmitic, palmitoleic, oleic, and arachidonic acids of the sausages. In contrast, AC reduced the level of fat (12.61%–87.56%) and energy (5.76%–56.40%) of the sausages. In addition, AC led to the mild lightness, yellowness, whiteness, and soft texture, while it did not affect the water activity of the sausages. From the sensory point of view, all sausages were judged acceptable, and the substitution of 75% of pork fat by AC exhibited best sensory characteristics. In a word, AC is a promising food to partially replace the pork fat in sausages.

Pork fat in sausage was replaced by tremella at different proportions during the process, and the physicochemical and sensory profiles of pork sausage were evaluated. Five recipes with the replacement proportion of 0%, 25%, 50%, 75%, and 100% tremella were manufactured, and their proximate compositions, water activities, textures, colors, water holding capacities (WHC), and amino acid compositions were investigated. The results showed that the protein, ash and moisture content, lightness, redness, and WHC of pork sausages were increased (p &lt, 0.05), and textural profile analysis (TPA) and sensory quality of the sausage were improved (p &lt, 0.05). In addition, the content of essential amino acids (lysine and isoleucine) and the non-essential amino acids (proline and tyrosine) of sausages were increased (p &lt, 0.05). The sausage had the best sensory performance when the replacement ratio of tremella was 75%. These results indicated that replacing fat with tremella could be a valid way to obtain nutritional and healthy sausage.

The tumor microenvironment (TME) is a unique niche governed by constant crosstalk within and across all intratumoral cellular compartments. In particular, intratumoral high potassium (K

The myocyte enhancer factor 2 (MEF2) factors act as lynchpins in cell differentiation and organogenesis through transcriptional circuits and thus potentiate development of vertebrate. Nevertheless, the association between mutations in Myocyte enhancer factor 2 (MEF2s) especially MEF2C (Myocyte enhancer factor 2C) and livestock growth remains largely unknown. Here, in Nanjiang Yellow goat population (female, n = 219), we identified 10 single nucleotide variations (SNVs) in MEF2C using direct Sanger sequencing PCR product from DNA and cDNA. Among which eight were located in exons while two (g.143180 T>G and g.143666 C>T) were in introns, and the only one mutation embedded in coding region (g. 143515 C>T) led to a Pro 148 Ser exchange. In this goat population, all these ten SNVs presented lower to moderate polymorphism (0.28 0.05). Notably, four SNVs including g.76303 A>G, g.143180 T>G, g.176090 A>G, and g.176845 T>C significantly associated with goat growth (p G variation even exceeded those H3H4 animals by over ~20% from birth to 12-mon old (p G variation exhibited no connection with exon α splicing of MEF2C, but in silicon analysis revealed that T to G mutation potentially increased DNA accessibility of g.143180 T>G per se and the following 14-bp region by 2 to 22 fold, which directly relates the binding of dlx5 (Distal-Less Homeobox 5). These results confirm the close relationship between MEF2C and animal development, and also provide an important option guiding study in elucidating the substantial mechanisms that MEF2C exerts in promoting mammal growth.

Chromoblastomycosis is a chronic cutaneous fungal infection caused by dematiaceous fungi. It is a therapeutic challenge because of the lack of specific treatments. We describe a refractory case of chromoblastomycosis in which the lesion did not respond to initial treatment, but then use of topical imiquimod cured the lesion successfully.

RFID technology not only enables wireless identification, it also provides the platform for battery-less antenna sensing capabilities, i.e., the sensing information is modulated by the antenna impedance, and it can later be extracted from the backscattered signals by the readers. However, antenna sensing is prone to interference and ambient environment impacts, such as distance variation and noise in the transmission path. These factors can cause amplitude and phase changes of the received signals, and deteriorate the quality of the sensing information. In this paper, we propose a deformation sensor that consists of two adjacent-placed RFID antennas. The impedance of the two antennas will be modulated differently under the bending condition, and the deformation information can be extracted from the differential backscattered signals of the two antennas. To be deployed as a wearable body gesture sensor, the two antennas are embroidered on apparel using conductive yarns. Experiments show that differential sensing signals can effectively eliminate the impact from ambient interference, while tracking the body gesture even under varying reading distances.

Background. Stage II colorectal cancer patients had heterogeneous prognosis, and patients with recurrent events had poor survival. In this study, we aimed to identify stage II colorectal cancer recurrence associated genes by microarray meta-analysis and build predictive models to stratify patients’ recurrence-free survival. Methods. We searched the GEO database to retrieve eligible microarray datasets. The microarray meta-analysis was used to identify universal recurrence associated genes. Total samples were randomly divided into the training set and the test set. Two survival models (lasso Cox model and random survival forest model) were trained in the training set, and AUC values of the time-dependent receiver operating characteristic (ROC) curves were calculated. Survival analysis was performed to determine whether there was significant difference between the predicted high and low risk groups in the test set. Results. Six datasets containing 651 stage II colorectal cancer patients were included in this study. The microarray meta-analysis identified 479 recurrence associated genes. KEGG and GO enrichment analysis showed that G protein-coupled glutamate receptor binding and Hedgehog signaling were significantly enriched. AUC values of the lasso Cox model and the random survival forest model were 0.815 and 0.993 at 60 months, respectively. In addition, the random survival forest model demonstrated that the effects of gene expression on the recurrence-free survival probability were nonlinear. According to the risk scores computed by the random survival forest model, the high risk group had significantly higher recurrence risk than the low risk group (HR = 1.824, 95% CI: 1.079–3.084, p = 0.025). Conclusions. We identified 479 stage II colorectal cancer recurrence associated genes by microarray meta-analysis. The random survival forest model which was based on the recurrence associated gene signature could strongly predict the recurrence risk of stage II colorectal cancer patients.

Additional file 4: Table S1. The stages of CRC patients and the corresponding exosomal ANGPTL1 index calculated by ImageJ from WB brands. The CRC stage was based on 7th revised edition of the AJCC Colorectal Cancer.

Background Angiopoietin-like protein 1 (ANGPTL1) has been proved to suppress tumor metastasis in several cancers. However, its extracellular effects on the pre-metastatic niches (PMNs) are still unclear. ANGPTL1 has been identified in exosomes, while its function remains unknown. This study was designed to explore the role of exosomal ANGPTL1 on liver metastasis in colorectal cancer (CRC). Methods Exosomes were isolated by ultracentrifugation. The ANGPTL1 level was detected in exosomes derived from human CRC tissues. The effects of exosomal ANGPTL1 on CRC liver metastasis were explored by the intrasplenic injection mouse model. The liver PMN was examined by vascular permeability assays. Exosomal ANGPTL1 localization was validated by exosome labeling. The regulatory mechanisms of exosomal ANGPTL1 on Kupffer cells were determined by RNA sequencing. qRT-PCR, Western Blot, and ELISA analysis were conducted to examine gene expressions at mRNA and protein levels. Results ANGPTL1 protein level was significantly downregulated in the exosomes derived from CRC tumors compared with paired normal tissues. Besides, exosomal ANGPTL1 attenuated liver metastasis and impeded vascular leakiness in the liver PMN. Moreover, exosomal ANGPTL1 was mainly taken up by KCs and regulated the KCs secretion pattern, enormously decreasing the MMP9 expression, which finally prevented the liver vascular leakiness. In mechanism, exosomal ANGPTL1 downregulated MMP9 level in KCs by inhibiting the JAK2-STAT3 signaling pathway. Conclusions Taken together, exosomal ANGPTL1 attenuated CRC liver metastasis and impeded vascular leakiness in the liver PMN by reprogramming the Kupffer cell and decreasing the MMP9 expression. This study suggests a suppression role of exosomal ANGPTL1 on CRC liver metastasis and expands the approach of ANGPTL1 functioning.

PSTPIP1-associated myeloid-related proteinaemia inflammatory (PAMI) syndrome has been described as a rare and distinct clinical phenotype of PSTPIP1-associated inflammatory diseases. We report PSTPIP1 mutation in both father and son who have leukopenia and acne-like lesions. Through whole-exome sequencing on blood DNA, it is found a heterozygous mutation of PSTPIP1 gene c.748G>A on the father and son. The diagnosis of PAMI is made based on DNA sequencing results and clinical characteristics of typical lesions, leukopenia, and the markedly increased serum S100A8/A9 (calprotectin).

Background: Angiopoietin-like protein 1 (ANGPTL1) has been proved to suppress tumor metastasis in several cancers. However, its extracellular effects on the pre-metastatic niches (PMNs) are still unclear. ANGPTL1 has been identified in exosomes, while its function remains unknown. This study was designed to explore the role of exosomal ANGPTL1 on liver metastasis in colorectal cancer (CRC).Methods: Exosomes were isolated by ultracentrifugation. The ANGPTL1 level was detected in exosomes derived from human CRC tissues. The effects of exosomal ANGPTL1 on CRC liver metastasis were explored by the intrasplenic injection mouse model. The liver PMN was examined by vascular permeability assays. Exosomal ANGPTL1 localization was validated by exosome labeling. The regulatory mechanisms of exosomal ANGPTL1 on Kupffer cells were determined by RNA sequencing. qRT-PCR, Western Blot, and ELISA analysis were conducted to examine gene expressions at mRNA and protein levels.Results: ANGPTL1 protein level was significantly downregulated in the exosomes derived from CRC tumors compared with paired normal tissues. Besides, exosomal ANGPTL1 attenuated liver metastasis and impeded vascular leakiness in the liver PMN. Moreover, exosomal ANGPTL1 were mainly taken up by KCs and regulated the KCs secretion pattern, especially decreasing the MMP9 expression, which finally prevented the liver vascular leakiness. In mechanism, exosomal ANGPTL1 downregulated MMP9 level in KCs by inhibiting the JAK2-STAT3 signaling pathway.Conclusions: Taken together, exosomal ANGPTL1 attenuated CRC liver metastasis and impeded vascular leakiness in the liver PMN by reprogramming the Kupffer cell and decreasing the MMP9 expression. This study suggests a suppression role of exosomal ANGPTL1 on CRC liver metastasis and expands the approach of ANGPTL1 functioning.

Background: Colorectal cancer (CRC) is the third most common malignancy in the world and metastasis is responsible for a major proportion of the cancer-related deaths in CRC patients.Aims: To construct machine learning models for predicting lymph node and distant metastases in colorectal cancer and analyze biological functions features of metastasis-related genes.Methods: RNA-seq and miRNA-seq data as well as corresponding clinical data from colon adenocarcinoma (COAD) and rectum adenocarcinoma (READ) were obtained from The Cancer Genome Atlas (TCGA) database. The differentially expressed RNAs (DE-RNAs) in non-LNM (N0) and LNM (N1/N2) as well as non-distant metastases (M0) and distant metastases (M1) were analyzed. Six machine learning models including logistic regression (LR), random forest (RF), support vector machine (SVM), Catboost, gradient boosting decision tree (GBDT), and artificial neural network (NN) were constructed to predict cancer metastasis and the feature genes of the optimal model were further analyzed by functional enrichment, protein-protein interaction (PPI) network, and drug-target analyses.Results: Differential RNA expression profiles of LNM and non-LNM as well as M0 vs. M1 were observed in both COAD and READ samples. NN model was determined to be the optimal model for predicting distant metastases, while Catboost and LR models were the optimal models for predicting LNM in COAD and READ samples, respectively. PPI analysis indicated that KIR2DL4, chemokine-related genes CXCL9/10/11/13 and CCL25, and gamma-aminobutyric acid (GABA) receptor genes (GABRR1, GABRB2 and GABRA3) were key genes in metastasis. In addition, atorvastatin and eszopiclone were identified as potential therapeutic agents as they target these genes.Conclusions: We constructed six machine learning models for predicting colorectal cancer metastases and identify the optimal model. We analyzed biological functions features of metastasis-related RNAs in colorectal cancer.

Background: Despite recent advance in immune therapy, great heterogeneity exists in colorectal cancer (CRC) patients’ outcome. In this study, we aimed to analyze the Immune-related gene (IRG) expression profiles from two independent public databases and develop an effective signature to forecast patients’ prognosis.Method: IRGs were collected from The Cancer Genome Atlas (TCGA) database to identify a prognostic genes signature, which was verified in Gene Expression Omnibus (GEO) database. Gene function enrichment and immune cell infiltration analyses were conducted. A prognostic nomogram was built incorporating the IRG signature with clinical risk factors.Results: The training and test datasets had 487 and 579 patients, respectively. A prognostic six-gene-signature (CCL22, LIMK1, MAPKAPK3, FLOT1, GPRC5B and IL20RB) was developed through feature selection, and yielded incredible differentiation between low and high-risk group in the training set (P < 0.001), which was confirmed in the test group (P < 0.001). The signature outperformed tumor staging regarding survival prediction. Go and KEGG functional annotation analysis suggested the signature were significantly enriched in metabolic process and regulation of immunity (P

Background: Colorectal cancer (CRC) is the third most common malignancy in the world and metastasis is responsible for a major proportion of the cancer-related deaths in CRC patients.Aims: To construct machine learning models for predicting lymph node and distant metastases in colorectal cancer and analyze biological functions features of metastasis-related genes.Methods: RNA-seq and miRNA-seq data as well as corresponding clinical data from colon adenocarcinoma (COAD) and rectum adenocarcinoma (READ) were obtained from The Cancer Genome Atlas (TCGA) database. The differentially expressed RNAs (DE-RNAs) in non-LNM (N0) and LNM (N1/N2) as well as non-distant metastases (M0) and distant metastases (M1) were analyzed. Six machine learning models including logistic regression (LR), random forest (RF), support vector machine (SVM), Catboost, gradient boosting decision tree (GBDT), and artificial neural network (NN) were constructed to predict cancer metastasis and the feature genes of the optimal model were further analyzed by functional enrichment, protein-protein interaction (PPI) network, and drug-target analyses.Results: Differential RNA expression profiles of LNM and non-LNM as well as M0 vs. M1 were observed in both COAD and READ samples. NN model was determined to be the optimal model for predicting distant metastases, while Catboost and LR models were the optimal models for predicting LNM in COAD and READ samples, respectively. PPI analysis indicated that KIR2DL4, chemokine-related genes CXCL9/10/11/13 and CCL25, and gamma-aminobutyric acid (GABA) receptor genes (GABRR1, GABRB2 and GABRA3) were key genes in metastasis. In addition, atorvastatin and eszopiclone were identified as potential therapeutic agents as they target these genes.Conclusions: We constructed six machine learning models for predicting colorectal cancer metastases and identify the optimal model. We analyzed biological functions features of metastasis-related RNAs in colorectal cancer.

Objective: The objective of this study was to identify key molecules including small nucleolar RNAs (snoRNAs) and small nucleolar RNA host genes (SNHGs) involved in pancreatic cancer.Methods: First, we screened the differentially expressed snoRNAs (DEsnoRNAs) and trend-related snoRNAs based on the cancer genome atlas (TCGA) dataset for pancreatic cancer, and then performed methylation correlation analysis, survival analysis, and extraction of snoRNA host genes for Gene ontology (GO) functional and the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis. Next, DESNHGs and trend-related SNHGs were screened according to the TCGA dataset for pancreatic cancer, and a competing endogenous RNA (ceRNA) network was constructed for pathway and functional enrichment analysis. Results: A total of eight DEsnoRNAs and 93 trend-related snoRNAs were extracted. Then, ten host genes of the snoRNAs were identified. Functional analysis suggested that the ten host genes were significantly enriched in several GO terms including mitotic chromosome condensation and endocytosis pathway. SNORA38B was considered to associate with survival and prognosis. The SNORD17 and SNORA11 were considered to negatively correlate with methylation. In addition, two trend-related SNHGs were extracted. Additionally, a ceRNA network was constructed with 11 miRNAs, one lncRNAs, and one mRNA. SNHG24 mainly correlated with GnRH secretion and neuroactive ligand-receptor interaction in pancreatic cancer. Conclusion: The identified snoRNAs and SNHGs could serve as potential markers for the early detection of pancreatic cancer.

Background New therapeutics are urgently needed for infectious diseases, especially for the fungal infection like Fonsecaea monophora. Photodynamic therapy has been showing antimicrobial activity on some pathogens. The combination of antimicrobial medicines and photodynamic therapy (PDT) might be a practical approach. However, whether the treatment of PDT could do benefits to the host immunity remains poorly documented. Results In this study, Galleria mellonella larvae were employed as a model organism to evaluate the activity of PDT, and also to investigate the regulation of humoral immunity by PDT. Photosensitizer 5-aminolevulinic acid (ALA) was applied to the G. mellonella infection model. It was found that ALA-mediated PDT was non-toxic to G. mellonella, and could extend the median survival of infected larvae from 3 days to 5.5 days. We observed that larval hemocytes inhibited the growth of Candida albicans and Staphylococcus aureus, without any contribution by ALA-PDT. Furthermore, the application of ALA-PDT demonstrated the immunomodulation of larval innate immunity as increased hemocyte density counting, cell morphological transformation, and sensitivity to pathogens. Conclusions G. mellonella could be considered as a useful model to study the immunoregulation of PDT. This model revealed that ALA-PDT positively defense against infections through inducing humoral immune responses of larvae.

Purpose: This study aimed to investigate the role of small nucleolar RNAs (snoRNAs) and their host genes (SNHGs) in tumorigenesis and progression of esophageal carcinoma (EC).Methods: RNA-seq data and clinical information for EC patients were obtained from The Cancer Genome Atlas database. Differentially expressed snoRNAs (DE-snoRNAs) and SNHGs (DE-SNHGs) between EC samples and normal controls were screened with the edgeR package, followed by the trend analysis with STEM. Survival analysis was performed using the Kaplan–Meier method with the log-rank test. Screening of co-expressed genes and functional enrichment analyses were performed with Pearson’s correlation analysis and enrichment analysis, respectively. Lastly, the co-expression and ceRNA networks were constructed.Results: A total of 19 DE-snoRNAs and nine DE-SNHGs were screened between EC samples and normal controls. Moreover, two snoRNA clusters related to the clinic stage were analyzed through trend analysis. Survival analysis results demonstrated that SNORA70D was significantly associated with the overall survival of EC patients (P=0.034). In addition, a co-regulation network that included six snoRNAs and 29 mRNAs was constructed. A ceRNA network comprised of five SNHGs, 11 mRNAs, and 38 miRNAs was constructed based on the top 50 relationship pairs. KEGG pathway enrichment analysis revealed that SNORA14B, SNORA47, SNORA71C, SNORD12B, and SNORD14E in the co-expression network were mainly enriched in the NOD−like receptor signaling pathway, and neuroactive ligand−receptor interaction pathway. SNHG23, SNHG3, SNHG17, SNHG4, and SNHG8 in the ceRNA regulation network were mainly enriched in calcium signaling pathway, cytokine−cytokine receptor interaction, and the extracellular matrix−receptor interaction pathway.Conclusion: The data revealed a series of snoRNAs, SNHGs, and pathways involved in EC carcinogenesis, which will provide a basis for understanding the underlying molecular mechanism of EC development.