Psychological Distress, Multicare Needs and Social Resource Utilisation of Family Caregivers of People With Dementia: A Descriptive-Correlational Study.

BACKGROUND: The population of people with dementia increases yearly, imposing a growing burden on family caregivers. Psychological distress impacts the mental health of family caregivers of people with dementia. Caregiver psychological distress can result in increased social resource utilisation and unmet multicare needs. PURPOSE: The study explored the psychological distress of family caregivers of people with dementia and examined the impact on social resource utilisation and multicare needs. METHODS: A descriptive-correlational study collected data in Taiwan from a cross-sectional sample of family caregivers of people with dementia using a self-report questionnaire. Data were analysed using linear and logistic regression. RESULTS: A total of 301 caregivers provided data for analysis. Nearly two-thirds of caregivers were female with a mean age of 57 years old (SD = 12). Over half of the family caregivers of people with dementia experienced mild-to-moderate psychological distress. The greater the psychological distress, the greater the probability of using social resources (1.09 times per 1-point increase, p = 0.002). Psychological distress was positively associated with the number of caregivers' care needs (ß = 0.371, p < 0.001). CONCLUSIONS: Findings of this study can assist healthcare professionals in better understanding the psychological distress and care needs of caregivers. Services designed to meet the needs of family caregivers will improve psychological distress.

Bidirectional linkage of DNA barcodes for the multiplexed mapping of higher-order protein interactions in cells.

Capturing the full complexity of the diverse hierarchical interactions in the protein interactome is challenging. Here we report a DNA-barcoding method for the multiplexed mapping of pairwise and higher-order protein interactions and their dynamics within cells. The method leverages antibodies conjugated with barcoded DNA strands that can bidirectionally hybridize and covalently link to linearize closely spaced interactions within individual 3D protein complexes, encoding and decoding the protein constituents and the interactions among them. By mapping protein interactions in cancer cells and normal cells, we found that tumour cells exhibit a larger diversity and abundance of protein complexes with higher-order interactions. In biopsies of human breast-cancer tissue, the method accurately identified the cancer subtype and revealed that higher-order protein interactions are associated with cancer aggressiveness.

Machine learning algorithms to predict colistin-induced nephrotoxicity from electronic health records in patients with multidrug-resistant Gram-negative infection.

OBJECTIVES: Colistin-induced nephrotoxicity prolongs hospitalisation and increases mortality. The study aimed to construct machine learning models to predict colistin-induced nephrotoxicity in patients with multidrug-resistant Gram-negative infection. METHODS: Patients receiving colistin from three hospitals in the Clinical Research Database were included. Data were divided into a derivation cohort (2011-2017) and a temporal validation cohort (2018-2020). Fifteen machine learning models were established by categorical boosting, light gradient boosting machine and random forest. Classifier performances were compared by the sensitivity, F1 score, Matthews correlation coefficient (MCC), area under the receiver operating characteristic (AUROC) curve, and area under the precision-recall curve (AUPRC). SHapley Additive exPlanations plots were drawn to understand feature importance and interactions. RESULTS: The study included 1392 patients, with 360 (36.4%) and 165 (40.9%) experiencing nephrotoxicity in the derivation and temporal validation cohorts, respectively. The categorical boosting with oversampling achieved the highest performance with a sensitivity of 0.860, an F1 score of 0.740, an MCC of 0.533, an AUROC curve of 0.823, and an AUPRC of 0.737. The feature importance demonstrated that the days of colistin use, cumulative dose, daily dose, latest C-reactive protein, and baseline haemoglobin were the most important risk factors, especially for vulnerable patients. A cutoff colistin dose of 4.0 mg/kg body weight/d was identified for patients at higher risk of nephrotoxicity. CONCLUSIONS: Machine learning techniques can be an early identification tool to predict colistin-induced nephrotoxicity. The observed interactions suggest a modification in dose adjustment guidelines. Future geographic and prospective validation studies are warranted to strengthen the real-world applicability.

Polarity-Mediated Antisolvent Control Enables Efficient Lanthanide-Based near-Infrared Perovskite LEDs.

Alloying lanthanide ions (Yb3+) into perovskite quantum dots (Yb3+:CsPb(Cl1-xBrx)3) is an effective method to achieve efficient near-infrared (NIR) luminescence (>950 nm). Increasing the Yb3+ alloying ratio in the perovskite matrix enhances the luminescence intensity of Yb3+ emission at 990 nm. However, high Yb3+ alloying (>15%) results in vacancy-induced inferior material stability. In this work, we developed a polarity-mediated antisolvent manipulation strategy to resolve the incompatibility between a high Yb3+ alloying ratio and inferior stability of Yb3+:CsPb(Cl1-xBrx)3. Precise control of solution polarity enables increased uniformity of the perovskite matrix with fewer trap densities. Employing this strategy, we obtain Yb3+:CsPb(Cl1-xBrx)3 with the highest Yb3+ alloying ratio of 30.2% and a 2-fold higher electroluminescence intensity at 990 nm. We lever the engineered Yb3+:CsPb(Cl1-xBrx)3 to fabricate NIR-LEDs, achieving a peak external quantum efficiency (EQE) of 8.5% at 990 nm: this represents the highest among perovskite NIR-LEDs with an emission wavelength above 950 nm.

Modulatory effects of dietary saturated fatty acids on platelet mitochondrial function following short-term exposure to ambient Particulate Matter (PM2.5).

Exposure to ambient fine particulate matter (PM2.5) was found to produce vascular injury, possibly by activating platelets within days after exposure. The aim of this study was to investigate the modulatory effects of dietary saturated fatty acids on platelet mitochondrial respiratory parameters following short-term inhalational exposure to PM2.5. A total of 22 healthy male volunteers were recruited from the Research Triangle area of North Carolina. Platelets were isolated from fresh whole blood samples and mitochondrial respiratory parameters were measured using an extracellular flux analyzer. Intake of saturated fat was averaged from multiple 24-hr dietary recalls. Daily ambient PM2.5 concentrations were obtained from ambient air quality monitoring stations. Correlation and ANOVA were used in data analyses, along with the pick-a-point method and the Johnson-Neyman technique for probing moderation. After controlling for age and omega-3 index, the intake of dietary saturated fatty acids after reaching 9.3% or higher of the total caloric intake significantly moderated the associations between PM2.5 exposure and several platelet mitochondrial respiratory parameters. In conclusion, dietary saturated fatty acids above 9.3% of total caloric intake influenced the relationship between short-term PM2.5 exposure and platelet mitochondrial respiration. Further research is needed to understand these associations and their implications for cardiovascular health.

Thickness-variation-insensitive near-infrared quantum dot LEDs.

In terms of tunable luminescence and high quantum efficiency, colloidal quantum dots (CQDs) are promising semiconductors for constructing near-infrared light-emitting diodes (NIR-LEDs). However, currently available NIR-LEDs are susceptible to variations in the emission layer thickness (EMLT), the highest external quantum efficiency (EQE) decreases to below 50% (relative to peak EQE) when the EMLT varies out of a narrow range of (±30 nm). This is due to the thickness-dependent carrier recombination rate and current density variation, resulting in batch-to-batch EQE fluctuations that limit LED reproducibility. Here we report efficient NIR-LEDs that exhibit EQE variations of less than 15% (relative to the champion EQE) over an EMLT range of 40-220 nm; the highest achievable EQE of ∼11.5% was obtained by encapsulating a 212 nm-thick CQD within a type-I inorganic shell to enhance the radiative recombination in the dots, resulting in a high photoluminescence quantum yield of 80%, and by post-treating the films with a bifunctional linking agent to improve and balance the hole and electron mobilities in the entire film (electron mobility: 8.23 × 10-3 cm2 V-1 s-1; hole mobility: 7.0 × 10-3 cm2 V-1 s-1). This work presents the first NIR-LEDs that exhibit EMLT-invariant EQE over an EMLT range of 40-220 nm, which represents the highest EQE among reported CQD NIR-LEDs with a QD thickness exceeding 100 nm.

Inhibition of Galectin-9 sensitizes tumors to anthracycline treatment via inducing antitumor immunity.

Anthracyclines are a class of conventionally and routinely used first-line chemotherapy drugs for cancer treatment. In addition to the direct cytotoxic effects, increasing evidence indicates that the efficacy of the drugs also depends on immunomodulatory effects with unknown mechanisms. Galectin-9 (Gal-9), a member of the ß-galactoside-binding protein family, has been demonstrated to induce T-cell death and promote immunosuppression in the tumor microenvironment. Here, we asked whether anthracycline-mediated immunomodulatory activity might be related to Gal-9. We found that combining doxorubicin with anti-Gal-9 therapy significantly inhibited tumor growth and prolonged overall survival in immune-competent syngeneic mouse models. Moreover, Gal-9 expression was increased in response to doxorubicin in various human and murine cancer cell lines. Mechanistically, doxorubicin induced tumoral Gal-9 by activating the STING/interferon ß pathway. Clinically, Gal-9 and p-STING levels were elevated in the tumor tissues of breast cancer patients treated with anthracyclines. Our study demonstrates Gal-9 upregulation in response to anthracyclines as a novel mechanism mediating immune escape and suggests targeting Gal-9 in combination with anthracyclines as a promising therapeutic strategy for cancer treatment.

Iodotrimethylsilane as a Reactive Ligand for Surface Etching and Passivation of Perovskite Nanocrystals toward Efficient Pure-red to Deep-red LEDs.

Resurfacing perovskite nanocrystals (NCs) with tight-binding and conductive ligands to resolve the dynamic ligands-surface interaction is the fundamental issue for their applications in perovskite light-emitting diodes (PeLEDs). Although various types of surface ligands have been proposed, these ligands either exhibit weak Lewis acid/base interactions or need high polar solvents for dissolution and passivation, resulting in a compromise in the efficiency and stability of PeLEDs. Herein, we report a chemically reactive agent (Iodotrimethylsilane, TMIS) to address the trade-off among conductivity, solubility and passivation using all-inorganic CsPbI3 NCs. The liquid TMIS ensures good solubility in non-polar solvents and reacts with oleate ligands and produces in situ HI for surface etching and passivation, enabling strong-binding ligands on the NCs surface. We report, as a result, red PeLEDs with an external quantum efficiency (EQE) of ≈23 %, which is 11.2-fold higher than the control, and is among the highest CsPbI3 PeLEDs. We further demonstrate the universality of this ligand strategy in the pure bromide system (CsPbBr3 ), and report EQE of ≈20 % at 640, 652, and 664 nm. This represents the first demonstration of a chemically reactive ligand strategy that applies to different systems and works effectively in red PeLEDs spanning emission from pure-red to deep-red.

The natural tannins oligomeric proanthocyanidins and punicalagin are potent inhibitors of infection by SARS-CoV-2.

The Coronavirus Disease 2019 (COVID-19) pandemic continues to infect people worldwide. While the vaccinated population has been increasing, the rising breakthrough infection persists in the vaccinated population. For living with the virus, the dietary guidelines to prevent virus infection are worthy of and timely to develop further. Tannic acid has been demonstrated to be an effective inhibitor of coronavirus and is under clinical trial. Here we found that two other members of the tannins family, oligomeric proanthocyanidins (OPCs) and punicalagin, are also potent inhibitors against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection with different mechanisms. OPCs and punicalagin showed inhibitory activity against omicron variants of SARS-CoV-2 infection. The water extractant of the grape seed was rich in OPCs and also exhibited the strongest inhibitory activities for viral entry of wild-type and other variants in vitro. Moreover, we evaluated the inhibitory activity of grape seed extractants (GSE) supplementation against SARS-CoV-2 viral entry in vivo and observed that serum samples from the healthy human subjects had suppressive activity against different variants of SARS-CoV-2 Vpp infection after taking GSE capsules. Our results suggest that natural tannins acted as potent inhibitors against SARS-CoV-2 infection, and GSE supplementation could serve as healthy food for infection prevention.

Since it first surfaced in late 2019, the COVID-19 pandemic has had a significant impact on people's lives. While several vaccines have been created, infections have not disappeared. This is largely due to new variants of the virus responsible for the disease (SARS-CoV-2) emerging, which current vaccines do not work as well against. Indeed, several reports suggest that protection from the omicron variant wanes as shortly as four to six months after vaccination. Therefore, other strategies are needed to reduce the risk of SARS-CoV-2 infections. In 2022, researchers discovered that tannic acid blocked two proteins that SARS-CoV-2 needs to enter and replicate inside human cells. Tannic acid is part of the tannin family, which includes natural molecules found in plant-based meals and beverages. Here, Chen et al. ­ including some of the researchers involved in the 2022 studies ­ set out to find whether two other tannins found in nature (OPCs and punicalagin) could also inhibit SARS-CoV-2. Chen et al. administered tannic acid, OPCs and punicalagin to human cells cultured in a laboratory that had been infected with SARS-CoV-2. This revealed that all three tannins suppress the activity of the same proteins required for viral entry and replication, but to varying degrees suggesting that they block SARS-CoV-2 infections via different mechanisms. The compounds were also able to inhibit different variants of the virus, including omicron, from infecting the lab-grown cells. Further experiments revealed that water extracted from seeded grapes, which contains high levels of OPCs, could also block SARS-CoV-2 entry in the cell culture system. To test this further, Chen et al. gave 18 healthy individuals capsules containing different concentrations of grape seed extract and collected samples of their serum. The serum samples suppressed entry of different variants of SARS-CoV-2 in the cell culture system, with serums from subjects that received the higher dose having the greatest effect. These findings suggest that naturally occurring tannins can suppress multiple variants of SARS-CoV-2 from entering and replicating in cells. Consuming supplements of grape seed extract could potentially reduce the risk of SARS-CoV-2 infections. However, further experiments, including clinical trials, are needed to test this possibility.

Deep learning of 2D-Restructured gene expression representations for improved low-sample therapeutic response prediction.

Clinical outcome prediction is important for stratified therapeutics. Machine learning (ML) and deep learning (DL) methods facilitate therapeutic response prediction from transcriptomic profiles of cells and clinical samples. Clinical transcriptomic DL is challenged by the low-sample sizes (34-286 subjects), high-dimensionality (up to 21,653 genes) and unordered nature of clinical transcriptomic data. The established methods rely on ML algorithms at accuracy levels of 0.6-0.8 AUC/ACC values. Low-sample DL algorithms are needed for enhanced prediction capability. Here, an unsupervised manifold-guided algorithm was employed for restructuring transcriptomic data into ordered image-like 2D-representations, followed by efficient DL of these 2D-representations with deep ConvNets. Our DL models significantly outperformed the state-of-the-art (SOTA) ML models on 82% of 17 low-sample benchmark datasets (53% with >0.05 AUC/ACC improvement). They are more robust than the SOTA models in cross-cohort prediction tasks, and in identifying robust biomarkers and response-dependent variational patterns consistent with experimental indications.

Decoding a cryptic mechanism of metronidazole resistance among globally disseminated fluoroquinolone-resistant Clostridioides difficile.

Severe outbreaks and deaths have been linked to the emergence and global spread of fluoroquinolone-resistant Clostridioides difficile over the past two decades. At the same time, metronidazole, a nitro-containing antibiotic, has shown decreasing clinical efficacy in treating C. difficile infection (CDI). Most metronidazole-resistant C. difficile exhibit an unusual resistance phenotype that can only be detected in susceptibility tests using molecularly intact heme. Here, we describe the mechanism underlying this trait. We find that most metronidazole-resistant C. difficile strains carry a T-to-G mutation (which we term PnimBG) in the promoter of gene nimB, resulting in constitutive transcription. Silencing or deleting nimB eliminates metronidazole resistance. NimB is related to Nim proteins that are known to confer resistance to nitroimidazoles. We show that NimB is a heme-dependent flavin enzyme that degrades nitroimidazoles to amines lacking antimicrobial activity. Furthermore, occurrence of the PnimBG mutation is associated with a Thr82Ile substitution in DNA gyrase that confers fluoroquinolone resistance in epidemic strains. Our findings suggest that the pandemic of fluoroquinolone-resistant C. difficile occurring over the past few decades has also been characterized by widespread resistance to metronidazole.

Should nails be locked dynamically or statically in atypical femoral fractures? - A radiological analysis of time to union and reoperations in 236 displaced fractures with 4 years average follow-up.

INTRODUCTION: Atypical femoral fractures (AFFs) are associated with delayed union and higher reoperation rates. Axial dynamization of intramedullary nails is hypothesized to reduce time-to-union (TTU) and fixation failure as compared to static locking. METHODS: Consecutive acutely displaced AFFs fixed with long intramedullary nails across five centres between 2006 and 2021 with a minimum postoperative follow-up of three months were retrospectively reviewed. The primary outcome was TTU, compared between AFFs treated with dynamically or statically locked intramedullary nails. Fracture union was defined as a modified Radiographic Union Score for Tibial fractures score of 13 or greater. Secondary outcomes involved revision surgery and treatment failure, defined as non-union beyond 18 months or revision internal fixation for mechanical reasons. RESULTS: A total of 236 AFFs (127 dynamically locked and 109 statically locked) were analysed with good interobserver reliability of fracture union assessment (intraclass correlation coefficient = 0.89; 95% CI = 0.82-0.98). AFFs treated with dynamized nails had significantly shorter median TTU (10.1 months; 95% CI = 9.24-10.96 vs 13.0 months; 95% CI = 10.60-15.40) (log-rank test, p = 0.019). Multivariate Cox regression revealed that dynamic locking was independently associated with greater likelihood of fracture union within 24 months (p = 0.009). Reoperations were less frequent in the dynamic locking group (18.9% vs 28.4%), although the difference was not statistically significant (p = 0.084). Static locking was an independent risk factor for reoperation (p = 0.049), as were varus reduction and lack of teriparatide use within three months of surgery. Static locking also demonstrated a higher frequency of treatment failure (39.4% vs 22.8%, p = 0.006) and was an independent predictor of treatment failure in logistic regression (p = 0.018). Other factors associated with treatment failure included varus reduction and open reduction. CONCLUSIONS: Dynamic locking of intramedullary nails in AFFs is associated with faster time to union, lower rate of non-union, and fewer treatment failures.

Efficient Near-Infrared Electroluminescence from Lanthanide-Doped Perovskite Quantum Cutters.

Perovskite nanocrystals (PeNCs) deliver size- and composition-tunable luminescence of high efficiency and color purity in the visible range. However, attaining efficient electroluminescence (EL) in the near-infrared (NIR) region from PeNCs is challenging, limiting their potential applications. Here we demonstrate a highly efficient NIR light-emitting diode (LED) by doping ytterbium ions into a PeNCs host (Yb3+ : PeNCs), extending the EL wavelengths toward 1000 nm, which is achieved through a direct sensitization of Yb3+ ions by the PeNC host. Efficient quantum-cutting processes enable high photoluminescence quantum yields (PLQYs) of up to 126 % from the Yb3+ : PeNCs. Through halide-composition engineering and surface passivation to improve both PLQY and charge-transport balance, we demonstrate an efficient NIR LED with a peak external quantum efficiency of 7.7 % at a central wavelength of 990 nm, representing the most efficient perovskite-based LEDs with emission wavelengths beyond 850 nm.

MiR-455-5p suppresses PDZK1IP1 to promote the motility of oral squamous cell carcinoma and accelerate clinical cancer invasion by regulating partial epithelial-to-mesenchymal transition.

BACKGROUND: Lymph node and distant metastasis contribute to poor outcomes in patients with oral squamous cell carcinoma (OSCC). The mechanisms regulating cancer migration and invasion play a key role in OSCC. METHODS: We determined migration and invasion ability of OSCC by wound-healing assay, two-chamber transwell invasion assay and cell mobility tracking and evaluated tumor metastasis in vivo. Western blot (WB), qRT-PCR, RNA-seq, dual-luciferase reporter assays and nuclear/cytoplasmic fractionation were performed to investigate the potential mechanism. Immunohistochimical (IHC) staining determined vimentin and PDZK1IP1 expression in OSCC tissues. RESULTS AND CONCLUSION: In this study, we determined that miR-455-5p was associated with lymph node metastasis and clinical invasion, leading to poor outcomes in patients with OSCC. MiR-455-5p promoted oral cancer cell migration and invasion and induced epithelial-to-mesenchymal transition (EMT). We also identified a new biomarker, PDZK1IP1 (MAP17), that was targeted by miR-455-5p. PDZK1IP1 knockdown led to migration, metastasis, EMT, and increased transforming growth factor-ß signaling in OSCC. In addition, miR-455-5p overexpression and PDZK1IP1 inhibition promoted collective OSCC cell migration. According to data from the Cancer Genome Atlas database and the NCKU-OrCA-40TN data set, miR-455-5p and PDZK1IP1 are positively and negatively correlated, respectively, with partial EMT score. High miR-455-5p expression was associated with high vimentin levels and low MAP17 H-scores. The patients with low MAP17 expression had higher rates of disease recurrence than did patients with high MAP17 expression, especially for patients with clinical invasion risk factors and low MAP17 expression. These results suggest that miR-455-5p suppresses PDZK1IP1 expression and mediates OSCC progression. MiR-455-5p and PDZK1IP1 may therefore serve as key biomarkers and be involved in regulating partial EMT in OSCC cells. PDZK1IP1 expression may also serve as an independent factor that impacts outcomes in patients with clinical risk factors for recurrence.

Enhanced metagenomic deep learning for disease prediction and consistent signature recognition by restructured microbiome 2D representations.

Metagenomic analysis has been explored for disease diagnosis and biomarker discovery. Low sample sizes, high dimensionality, and sparsity of metagenomic data challenge metagenomic investigations. Here, an unsupervised microbial embedding, grouping, and mapping algorithm (MEGMA) was developed to transform metagenomic data into individualized multichannel microbiome 2D representation by manifold learning and clustering of microbial profiles (e.g., composition, abundance, hierarchy, and taxonomy). These 2D representations enable enhanced disease prediction by established ConvNet-based AggMapNet models, outperforming the commonly used machine learning and deep learning models in metagenomic benchmark datasets. These 2D representations combined with AggMapNet explainable module robustly identified more reliable and replicable disease-prediction microbes (biomarkers). Employing the MEGMA-AggMapNet pipeline for biomarker identification from 5 disease datasets, 84% of the identified biomarkers have been described in over 74 distinct works as important for these diseases. Moreover, the method also discovered highly consistent sets of biomarkers in cross-cohort colorectal cancer (CRC) patients and microbial shifts in different CRC stages.

Toward ordered -omics data science: Researchers on the magic of turning metagenomic chaos into image-like patterns.

Wan Xiang Shen, a postdoctoral researcher at National University of Singapore, and Yu Zong Chen, the PI of the Bioinformatics and Drug Design (BIDD) group, have developed an AI pipeline for enhanced deep learning of metagenomic data. Their Patterns paper highlights the advantages of unsupervised data restructuring in microbiome-based disease prediction and biomarker discovery. They talk about their view of data science and the backstory of the article published in Patterns.

14-3-3ζ inhibits maladaptive repair in renal tubules by regulating YAP and reduces renal interstitial fibrosis.

Acute kidney injury (AKI) refers to a group of common clinical syndromes characterized by acute renal dysfunction, which may lead to chronic kidney disease (CKD), and this process is called the AKI-CKD transition. The transcriptional coactivator YAP can promote the AKI-CKD transition by regulating the expression of profibrotic factors, and 14-3-3 protein zeta (14-3-3ζ), an important regulatory protein of YAP, may prevent the AKI-CKD transition. We established an AKI-CKD model in mice by unilateral renal ischemia-reperfusion injury and overexpressed 14-3-3ζ in mice using a fluid dynamics-based gene transfection technique. We also overexpressed and knocked down 14-3-3ζ in vitro. In AKI-CKD model mice, 14-3-3ζ expression was significantly increased at the AKI stage. During the development of chronic disease, the expression of 14-3-3ζ tended to decrease, whereas active YAP was consistently overexpressed. In vitro, we found that 14-3-3ζ can combine with YAP, promote the phosphorylation of YAP, inhibit YAP nuclear translocation, and reduce the expression of fibrosis-related proteins. In an in vivo intervention experiment, we found that the overexpression of 14-3-3ζ slowed the process of renal fibrosis in a mouse model of AKI-CKD. These findings suggest that 14-3-3ζ can affect the expression of fibrosis-related proteins by regulating YAP, inhibit the maladaptive repair of renal tubular epithelial cells, and prevent the AKI-CKD transition.

Interruption of the long non-coding RNA HOTAIR signaling axis ameliorates chemotherapy-induced cachexia in bladder cancer.

BACKGROUND: Cisplatin-based chemotherapy is the first line of treatment for bladder cancer. However, cisplatin induces muscle wasting associated with NF-κB and cancer cachexia. HOTAIR, an oncogenic long non-coding RNA (lncRNA), promotes cancer progression in different cancers. Crosstalk between HOTAIR and NF-κB is documented. Prothymosin α (ProT) plays important roles in cancer progression and inflammation. However, the potential link between HOTAIR, ProT, and cisplatin-induced cancer cachexia remains unexplored. Here, we investigated the contribution of HOTAIR in cisplatin-induced cancer cachexia and dissected the potential signaling cascade involving the epidermal growth factor receptor (EGFR), ProT, NF-κB, and HOTAIR. MATERIALS AND METHODS: Expression of ProT and HOTAIR transcripts and their correlations in tumor tissues of bladder cancer patients and bladder cancer cell lines were determined by RT-qPCR. Next, levels of phospho-EGFR, EGFR, phospho-NF-κB, and NF-κB were examined by immunoblot analysis in human bladder cancer cells treated with cisplatin. Expression of HOTAIR in cisplatin-treated cells was also assessed by RT-qPCR. Pharmacological inhibitors and overexpression and knockdown approaches were exploited to decipher the signaling pathway. The murine C2C12 myoblasts were used as an in vitro muscle atrophy model. The syngeneic murine MBT-2 bladder tumor was used to investigate the role of mouse Hotair in cisplatin-induced cancer cachexia. RESULTS: Expression of ProT and HOTAIR was higher in bladder tumors than in normal adjacent tissues. There were positive correlations between ProT and HOTAIR expression in clinical bladder tumors and bladder cancer cell lines. Cisplatin treatment increased EGFR and NF-κB activation and upregulated ProT and HOTAIR expression in bladder cancer cells. ProT overexpression increased, whereas ProT knockdown decreased, HOTAIR expression. Notably, cisplatin-induced HOTAIR upregulation was abrogated by EGFR inhibitors or ProT knockdown. ProT-induced HOTAIR overexpression was diminished by NF-κB inhibitors. HOTAIR overexpression enhanced, whereas its knockdown reduced, cell proliferation, cachexia-associated pro-inflammatory cytokine expression, and muscle atrophy. Cachexia-associated symptoms were ameliorated in mice bearing Hotair-knockdown bladder tumors undergoing cisplatin treatment. CONCLUSIONS: We demonstrate for the first time a critical role for HOTAIR and identify the involvement of the EGFR-ProT-NF-κB-HOTAIR signaling axis in cisplatin-induced cachexia in bladder cancer and likely other cancers. Our findings also provide therapeutic targets for this disease.

Novel Potential Therapeutic Targets of PTPN Families for Lung Cancer.

Despite the treatment of lung adenocarcinoma (LUAD) having partially improved in recent years, LUAD patients still have poor prognosis rates. Therefore, it is especially important to explore effective biomarkers and exploit novel therapeutic developments. High-throughput technologies are widely used as systematic approaches to explore differences in expressions of thousands of genes for both biological and genomic systems. Recently, using big data analyses in biomedicine research by integrating several high-throughput databases and tools, including The Cancer Genome Atlas (TCGA), cBioportal, Oncomine, and Kaplan-Meier plotter, is an important strategy to identify novel biomarkers for cancer therapy. Here, we used two different comprehensive bioinformatics analysis and revealed protein tyrosine phosphatase non-receptor type (PTPN) family genes, especially PTPN1 and PTPN22, were downregulated in lung cancer tissue in comparison with normal samples. The survival curves indicated that LUAD patients with high transcription levels of PTPN5 were significantly associated with a good prognosis. Meanwhile, Gene Ontology (GO) and MetaCore analyses indicated that co-expression of the PTPN1, PTPN5, and PTPN21 genes was significantly enriched in cancer development-related pathways, including GTPase activity, regulation of small GTPase-mediated signal transduction, response to mechanical stimuli, vasculogenesis, organ morphogenesis, regulation of stress fiber assembly, mitogen-activated protein kinase (MAPK) cascade, cell migration, and angiogenesis. Collectively, this study revealed that PTPN family members are both significant prognostic biomarkers for lung cancer progression and promising clinical therapeutic targets, which provide new targets for treating LUAD patients.