Acupuncture for Low Back Pain: Reevaluation of Systematic Reviews and Meta-analyses.

PURPOSE OF REVIEW: This overview aims to reevaluate the methodological quality, report quality, and evidence quality of systematic reviews (SRs)/meta-analyses (MAs) of acupuncture for low back pain to determine whether acupuncture effectively treats low back pain (LBP). RECENT FINDINGS: Twenty-three SRs/MAs were deemed eligible for the present overview. The AMSTAR 2 score showed that the methodological quality of one SR/MA was of medium quality, one was of low quality, and 21 were of critically low quality. Based on the results of the PRISMA evaluation, there are certain areas for improvement in the quality of reporting of SRs/MAs. There were some reporting flaws in the topic of search strategy (8/23, 34.78%), certainty assessment (4/23, 17.39%), the certainty of evidence (4/23, 17.39%), registration and protocol (3/23, 13.04%), and availability of data, code, and other material (1/23, 4.35%). Results from the GRADE evaluation indicated that 13 of 255 outcomes were rated as moderate, 88 were low, and 154 were very low. Acupuncture effectively treated LBP in the SRs/MAs included in the reevaluation. However, the methodological, report, and evidence-based quality of the SRs/MAs on acupuncture for LBP was low. Therefore, further rigorous and comprehensive studies are warranted to improve the quality of SRs/MAs in this field.

Identification of a prognostic gene signature of colon cancer using integrated bioinformatics analysis.

BACKGROUND: Colon cancer is a worldwide leading cause of cancer-related mortality, and the prognosis of colon cancer is still needed to be improved. This study aimed to construct a prognostic model for predicting the prognosis of colon cancer. METHODS: The gene expression profile data of colon cancer were obtained from the TCGA, GSE44861, and GSE44076 datasets. The WGCNA module genes and common differentially expressed genes (DEGs) were used to screen out the prognosis-associated DEGs, which were used to construct a prognostic model. The performance of the prognostic model was assessed and validated in the TCGA training and microarray validation sets (GSE38832 and GSE17538). At last, the model and prognosis-associated clinical factors were used for the construction of the nomogram. RESULTS: Five colon cancer-related WGCNA modules (including 1160 genes) and 1153 DEGs between tumor and normal tissues were identified, inclusive of 556 overlapping DEGs. Stepwise Cox regression analyses identified there were 14 prognosis-associated DEGs, of which 12 DEGs were included in the optimized prognostic gene signature. This prognostic model presented a high forecast ability for the prognosis of colon cancer both in the TCGA training dataset and the validation datasets (GSE38832 and GSE17538; AUC > 0.8). In addition, patients' age, T classification, recurrence status, and prognostic risk score were associated with the prognosis of TCGA patients with colon cancer. The nomogram was constructed using the above factors, and the predictive 3- and 5-year survival probabilities had high compliance with the actual survival proportions. CONCLUSIONS: The 12-gene signature prognostic model had a high predictive ability for the prognosis of colon cancer.

Traditional Chinese medicine paraffin therapy: an evidence-based overview from a modern medicine perspective.

External therapy of traditional Chinese medicine and paraffin therapy are both traditional Chinese forms of treatment. In recent years, external use of traditional Chinese medicine combined with paraffin therapy, which involves combining meridians, acupoints, drugs, and hyperthermia, has demonstrated great effectiveness in treating certain conditions. An overview of traditional Chinese medicine paraffin therapy (TCMPT) is provided by this article. Additionally, this article describes a new classification of TCMPT, mechanism of action, clinical treatment, indications contraindications and adverse events reports.

Dual-engineered, "Trojanized" macrophages bio-modally eradicate tumors through biologically and photothermally deconstructing cancer cells in an on-demand, NIR-commanded, self-explosive manner.

To engineer tumor-tropic cells as drug delivery vehicles is a promising strategy to improve therapeutic specificity and efficacy for cancer treatment. However, conventional genetically engineered cell-based drug delivery systems are often capable of initiating single-mode therapy, and lack precise spatiotemporal control over the release of therapeutic payloads at tumor local, thus possibly causing severe systemic toxicity. Here, the macrophages are genetically engineered to encode a non-secreted form of EGFP-TNFα fusion protein and intracellularly carry near-infrared (NIR)-responsive heat-nanogenerators (HIMs). Owing to macrophages' intrinsic tumor tropism and HIMs' photo-responsiveness to NIR, these macrophages (HIMs@eMET) can actively accumulate at tumor sites and undergo controlled photothermolysis induced by NIR-induced HIMs-mediated photothermal effects (PTE). Such heat-induced cell explosion enables spatiotemporally controlled release of non-secreted TNFα from macrophages and effectively kills cancer cells. Importantly, in a preclinical tumor model, HIMs@eMET actively migrate to tumors where PTE and released EGFP-TNFα exhibit an enhanced antitumor effect, suppressing tumor growth and significantly prolonging animal survival without eliciting adverse side effects. Thus, this study demonstrates the potential of such dual-engineered macrophages in bi-modal cancer therapy.