Purpose: Diagnosing sarcopenia necessitates the measurement of skeletal muscle mass. However, guidelines lack a standardized imaging modality with thresholds validated among Asians. This systematic review compared ultrasonography, computed tomography (CT), magnetic resonance imaging (MRI), and bioelectrical impedance analysis (BIA)/body composition monitoring in the detection of sarcopenia within Asian populations. Methods: PubMed and Embase were systematically searched for studies analyzing ultrasonography, CT, MRI, and BIA in diagnosing sarcopenia among Asians. Study quality was assessed using the Newcastle-Ottawa scale. Results: Pooled findings from 21,598 patients across 25 studies were examined. In receiver operating characteristic analysis, ultrasound displayed a pooled mean area under the curve (AUC) of 0.767 (95% confidence interval [CI], 0.709–0.806), with mean sensitivity of 81.1% (95% CI, 0.744–0.846) and specificity of 73.1% (95% CI, 0.648–0.774), for detecting sarcopenia in Asian populations. CT exhibited an AUC of 0.720 (sensitivity, 54.0%; specificity, 92.0%). MRI demonstrated an AUC of 0.839 (sensitivity, 67.0%; specificity, 66.0%). BIA displayed an AUC of 0.905 (95% CI, 0.842–0.968), 80.7% sensitivity (95% CI, 0.129–0.679), and 82.4% specificity (95% CI, 0.191–0.633). Conclusion Various modalities aid in diagnosing sarcopenia, and selection should be individualized. Although only BIA and dual-energy x-ray absorptiometry are recommended by the Asian Working Group for Sarcopenia and the European Working Group on Sarcopenia in Older People, ultrasound imaging may hold diagnostic value for sarcopenia in the Asian population. In certain groups, diagnostic use of CT and MRI is warranted. Future research can standardize and validate modality-specific thresholds and protocols within Asian populations.

Purpose: Diagnosing sarcopenia necessitates the measurement of skeletal muscle mass. However, guidelines lack a standardized imaging modality with thresholds validated among Asians. This systematic review compared ultrasonography, computed tomography (CT), magnetic resonance imaging (MRI), and bioelectrical impedance analysis (BIA)/body composition monitoring in the detection of sarcopenia within Asian populations. Methods: PubMed and Embase were systematically searched for studies analyzing ultrasonography, CT, MRI, and BIA in diagnosing sarcopenia among Asians. Study quality was assessed using the Newcastle-Ottawa scale. Results: Pooled findings from 21,598 patients across 25 studies were examined. In receiver operating characteristic analysis, ultrasound displayed a pooled mean area under the curve (AUC) of 0.767 (95% confidence interval [CI], 0.709–0.806), with mean sensitivity of 81.1% (95% CI, 0.744–0.846) and specificity of 73.1% (95% CI, 0.648–0.774), for detecting sarcopenia in Asian populations. CT exhibited an AUC of 0.720 (sensitivity, 54.0%; specificity, 92.0%). MRI demonstrated an AUC of 0.839 (sensitivity, 67.0%; specificity, 66.0%). BIA displayed an AUC of 0.905 (95% CI, 0.842–0.968), 80.7% sensitivity (95% CI, 0.129–0.679), and 82.4% specificity (95% CI, 0.191–0.633). Conclusion Various modalities aid in diagnosing sarcopenia, and selection should be individualized. Although only BIA and dual-energy x-ray absorptiometry are recommended by the Asian Working Group for Sarcopenia and the European Working Group on Sarcopenia in Older People, ultrasound imaging may hold diagnostic value for sarcopenia in the Asian population. In certain groups, diagnostic use of CT and MRI is warranted. Future research can standardize and validate modality-specific thresholds and protocols within Asian populations.

Purpose: Diagnosing sarcopenia necessitates the measurement of skeletal muscle mass. However, guidelines lack a standardized imaging modality with thresholds validated among Asians. This systematic review compared ultrasonography, computed tomography (CT), magnetic resonance imaging (MRI), and bioelectrical impedance analysis (BIA)/body composition monitoring in the detection of sarcopenia within Asian populations. Methods: PubMed and Embase were systematically searched for studies analyzing ultrasonography, CT, MRI, and BIA in diagnosing sarcopenia among Asians. Study quality was assessed using the Newcastle-Ottawa scale. Results: Pooled findings from 21,598 patients across 25 studies were examined. In receiver operating characteristic analysis, ultrasound displayed a pooled mean area under the curve (AUC) of 0.767 (95% confidence interval [CI], 0.709–0.806), with mean sensitivity of 81.1% (95% CI, 0.744–0.846) and specificity of 73.1% (95% CI, 0.648–0.774), for detecting sarcopenia in Asian populations. CT exhibited an AUC of 0.720 (sensitivity, 54.0%; specificity, 92.0%). MRI demonstrated an AUC of 0.839 (sensitivity, 67.0%; specificity, 66.0%). BIA displayed an AUC of 0.905 (95% CI, 0.842–0.968), 80.7% sensitivity (95% CI, 0.129–0.679), and 82.4% specificity (95% CI, 0.191–0.633). Conclusion Various modalities aid in diagnosing sarcopenia, and selection should be individualized. Although only BIA and dual-energy x-ray absorptiometry are recommended by the Asian Working Group for Sarcopenia and the European Working Group on Sarcopenia in Older People, ultrasound imaging may hold diagnostic value for sarcopenia in the Asian population. In certain groups, diagnostic use of CT and MRI is warranted. Future research can standardize and validate modality-specific thresholds and protocols within Asian populations.

Purpose: Diagnosing sarcopenia necessitates the measurement of skeletal muscle mass. However, guidelines lack a standardized imaging modality with thresholds validated among Asians. This systematic review compared ultrasonography, computed tomography (CT), magnetic resonance imaging (MRI), and bioelectrical impedance analysis (BIA)/body composition monitoring in the detection of sarcopenia within Asian populations. Methods: PubMed and Embase were systematically searched for studies analyzing ultrasonography, CT, MRI, and BIA in diagnosing sarcopenia among Asians. Study quality was assessed using the Newcastle-Ottawa scale. Results: Pooled findings from 21,598 patients across 25 studies were examined. In receiver operating characteristic analysis, ultrasound displayed a pooled mean area under the curve (AUC) of 0.767 (95% confidence interval [CI], 0.709–0.806), with mean sensitivity of 81.1% (95% CI, 0.744–0.846) and specificity of 73.1% (95% CI, 0.648–0.774), for detecting sarcopenia in Asian populations. CT exhibited an AUC of 0.720 (sensitivity, 54.0%; specificity, 92.0%). MRI demonstrated an AUC of 0.839 (sensitivity, 67.0%; specificity, 66.0%). BIA displayed an AUC of 0.905 (95% CI, 0.842–0.968), 80.7% sensitivity (95% CI, 0.129–0.679), and 82.4% specificity (95% CI, 0.191–0.633). Conclusion Various modalities aid in diagnosing sarcopenia, and selection should be individualized. Although only BIA and dual-energy x-ray absorptiometry are recommended by the Asian Working Group for Sarcopenia and the European Working Group on Sarcopenia in Older People, ultrasound imaging may hold diagnostic value for sarcopenia in the Asian population. In certain groups, diagnostic use of CT and MRI is warranted. Future research can standardize and validate modality-specific thresholds and protocols within Asian populations.

Purpose: Diagnosing sarcopenia necessitates the measurement of skeletal muscle mass. However, guidelines lack a standardized imaging modality with thresholds validated among Asians. This systematic review compared ultrasonography, computed tomography (CT), magnetic resonance imaging (MRI), and bioelectrical impedance analysis (BIA)/body composition monitoring in the detection of sarcopenia within Asian populations. Methods: PubMed and Embase were systematically searched for studies analyzing ultrasonography, CT, MRI, and BIA in diagnosing sarcopenia among Asians. Study quality was assessed using the Newcastle-Ottawa scale. Results: Pooled findings from 21,598 patients across 25 studies were examined. In receiver operating characteristic analysis, ultrasound displayed a pooled mean area under the curve (AUC) of 0.767 (95% confidence interval [CI], 0.709–0.806), with mean sensitivity of 81.1% (95% CI, 0.744–0.846) and specificity of 73.1% (95% CI, 0.648–0.774), for detecting sarcopenia in Asian populations. CT exhibited an AUC of 0.720 (sensitivity, 54.0%; specificity, 92.0%). MRI demonstrated an AUC of 0.839 (sensitivity, 67.0%; specificity, 66.0%). BIA displayed an AUC of 0.905 (95% CI, 0.842–0.968), 80.7% sensitivity (95% CI, 0.129–0.679), and 82.4% specificity (95% CI, 0.191–0.633). Conclusion Various modalities aid in diagnosing sarcopenia, and selection should be individualized. Although only BIA and dual-energy x-ray absorptiometry are recommended by the Asian Working Group for Sarcopenia and the European Working Group on Sarcopenia in Older People, ultrasound imaging may hold diagnostic value for sarcopenia in the Asian population. In certain groups, diagnostic use of CT and MRI is warranted. Future research can standardize and validate modality-specific thresholds and protocols within Asian populations.

ObjectiveTransfer RNA-derived fragments (tRFs) are a recently characterized and rapidly expanding class of small non-coding RNAs, typically ranging from 13 to 50 nucleotides in length. They are derived from mature or precursor tRNA molecules through specific cleavage events and have been implicated in a wide range of cellular processes. Increasing evidence indicates that tRFs play important regulatory roles in gene expression, primarily by interacting with target messenger RNAs (mRNAs) to induce transcript degradation, in a manner partially analogous to microRNAs (miRNAs). However, despite their emerging biological relevance and potential roles in disease mechanisms, there remains a significant lack of computational tools capable of systematically predicting the interaction landscape between tRFs and their target mRNAs. Existing databases often rely on limited interaction features and lack the flexibility to accommodate novel or user-defined tRF sequences. The primary goal of this study was to develop a machine learning based prediction algorithm that enables high-throughput, accurate identification of tRF:mRNA binding events, thereby facilitating the functional analysis of tRF regulatory networks. MethodsWe began by assembling a manually curated dataset of 38 687 experimentally verified tRF:mRNA interaction pairs and extracting seven biologically informed features for each pair: (1) AU content of the binding site, (2) site pairing status, (3) binding region location, (4) number of binding sites per mRNA, (5) length of the longest consecutive complementary stretch, (6) total binding region length, and (7) seed sequence complementarity. Using this dataset and feature set, we trained 4 distinct machine learning classifiers—logistic regression, random forest, decision tree, and a multilayer perceptron (MLP)—to compare their ability to discriminate true interactions from non-interactions. Each model’s performance was evaluated using overall accuracy, receiver operating characteristic (ROC) curves, and the corresponding area under the ROC curve (AUC). The MLP consistently achieved the highest AUC among the four, and was therefore selected as the backbone of our prediction framework, which we named tRF Prospect. For biological validation, we retrieved 3 high-throughput RNA-seq datasets from the gene expression omnibus (GEO) in which individual tRFs were overexpressed: AS-tDR-007333 (GSE184690), tRF-3004b (GSE197091), and tRF-20-S998LO9D (GSE208381). Differential expression analysis of each dataset identified genes downregulated upon tRF overexpression, which we designated as putative targets. We then compared the predictions generated by tRF Prospect against those from three established tools—tRFTar, tRForest, and tRFTarget—by quantifying the number of predicted targets for each tRF and assessing concordance with the experimentally derived gene sets. ResultsThe proposed algorithm achieved high predictive accuracy, with an AUC of 0.934. Functional validation was conducted using transcriptome-wide RNA-seq datasets from cells overexpressing specific tRFs, confirming the model’s ability to accurately predict biologically relevant downregulation of mRNA targets. When benchmarked against established tools such as tRFTar, tRForest, and tRFTarget, tRF Prospect consistently demonstrated superior performance, both in terms of predictive precision and sensitivity, as well as in identifying a higher number of true-positive interactions. Moreover, unlike static databases that are limited to precomputed results, tRF Prospect supports real-time prediction for any user-defined tRF sequence, enhancing its applicability in exploratory and hypothesis-driven research. ConclusionThis study introduces tRF Prospect as a powerful and flexible computational tool for investigating tRF:mRNA interactions. By leveraging the predictive strength of deep learning and incorporating a broad spectrum of interaction-relevant features, it addresses key limitations of existing platforms. Specifically, tRF Prospect: (1) expands the range of detectable tRF and target types; (2) improves prediction accuracy through multilayer perceptron model; and (3) allows for dynamic, user-driven analysis beyond database constraints. Although the current version emphasizes miRNA-like repression mechanisms and faces challenges in accurately capturing 5'UTR-associated binding events, it nonetheless provides a critical foundation for future studies aiming to unravel the complex roles of tRFs in gene regulation, cellular function, and disease pathogenesis.

INTRODUCTION: Radiofrequency ablation (RFA) avoids the complications of general anaesthesia, reduces length of hospitalisation and reduces morbidity from surgery. As such, it is a strong alternative treatment for patients with comorbidities who are not surgical candidates. However, to our knowledge, there have only been 1 systematic review and 3 combined systematic review and meta-analyses on this topic to date. This systematic review and meta-analysis seeks to evaluate the efficacy and safety of RFA in the treatment of papillary thyroid carcinoma (PTC) with longer follow-up durations. METHOD: PubMed, Embase and Cochrane databases were searched for relevant studies published from 1990 to 2021; 13 studies with a total of 1366 patients were included. The Preferred Reporting Items for Systematic reviews and Meta-Analyses guidelines and Sandelowski et al.'s approach1 to "negotiated consensual validation" were used to achieve consensus on the final list of articles to be included. All authors then assessed each study using a rating scheme modified from the Oxford Centre for Evidence-Based Medicine. RESULTS: Pooled volume reduction rates (VRRs) from 1 to 48 months after RFA, complete disappearance rates (CDR) and complications were assessed. Pooled mean VRRs were 96.59 (95% confidence interval [CI] 91.05-102.13, I2=0%) at 12 months2-6 and 99.31 (95% CI 93.74-104.88, I2=not applicable) at 48 months.2,5 Five studies showed an eventual CDR of 100%.2,4,7-9 No life-threatening complications were recorded. The most common complications included pain, transient voice hoarseness, fever and less commonly, first-degree burn. CONCLUSION RFA may be an effective and safe alternative to treating PTC. Larger clinical trials with longer follow-up are needed to further evaluate the effectiveness of RFA in treating PTC.
Humans ; Radiofrequency Ablation/methods* ; Thyroid Cancer, Papillary/surgery* ; Thyroid Neoplasms/surgery* ; Treatment Outcome ; Postoperative Complications/etiology*

INTRODUCTION: Trastuzumab deruxtecan (T-DXd) has revolutionised treatment for metastatic breast cancer (MBC). While effective, its high cost and toxicities, such as fatigue and nausea, pose challenges. METHOD: Medical records from the Joint Breast Cancer Registry in Singapore were used to study MBC patients treated with T-DXd (February 2021-June 2024). This study was conducted to address whether reducing dose intensity and density may have an adverse effect on treatment outcomes. RESULTS: Eighty-seven MBC patients were treated with T-DXd, with a median age of 59 years. At the time of data cutoff, 32.1% of patients were still receiving T-DXd. Over half (54%) of the patients received treatment with an initial relative dose intensity (RDI) of <;85%. Overall median real-world progression-free survival (rwPFS) was 8.1 months. rwPFS was similar between RDI groups (<85%: 8.7 months, <85%: 8.1 months, P=0.62). However, human epidermal growth receptor 2 (HER2)-positive patients showed significantly better rwPFS outcomes compared to HER2-low patients (8.8 versus 2.5 months, P<0.001). Only 16% with central nervous system (CNS) involvement had CNS progressive disease on treatment. No significant progression-free survival (PFS) differences were found between patients with or without CNS disease, regardless of RDI groups. Five patients (5.7%) developed interstitial lung disease (ILD), with 3 (3.4%) having grade 3 events. Two required high-dose steroids and none were rechallenged after ILD. There were no fatalities. CONCLUSION Our study demonstrated that reduced dose intensity and density had no significant impact on rwPFS or treatment-related toxicities. Furthermore, only 5.7% of patients developed ILD. T-Dxd provided good control of CNS disease, with 82% of patients achieving CNS disease control.
Humans ; Female ; Breast Neoplasms/mortality* ; Middle Aged ; Trastuzumab/adverse effects* ; Aged ; Adult ; Singapore/epidemiology* ; Antineoplastic Agents, Immunological/adverse effects* ; Camptothecin/adverse effects* ; Immunoconjugates/adverse effects* ; Retrospective Studies ; Progression-Free Survival ; Receptor, ErbB-2/metabolism* ; Neoplasm Metastasis ; Dose-Response Relationship, Drug ; Treatment Outcome ; Registries

The effect of Huanglian Jiedu Decoction on the intestinal flora of type 2 diabetes mellitus(T2DM) was investigated using 16S rRNA sequencing technology. Sixty rats were randomly divided into a normal group(10 rats) and a modeling group(50 rats). After one week of adaptive feeding, a high-fat diet + streptozotocin was given for modeling, and fasting blood glucose >16.7 mmol·L~(-1) was considered a sign of successful modeling. The modeling group was randomly divided into the model group, high-, medium-, and low-dose groups of Huanglian Jiedu Decoction, and metformin group. After seven days of intragastric treatment, the feces, colon, and pancreatic tissue of each group of rats were collected, and the pathological changes of the colon and pancreatic tissue of each group were observed by hematoxylin-eosin staining. The changes in the intestinal flora structure of each group were observed by the 16S rRNA sequencing method. The results showed that compared with the model group, the high-, medium-, and low-dose of Huanglian Jiedu Decoction reduced fasting blood glucose levels to different degrees and showed no significant changes in body weight. The number of islet cells increased, and intestinal mucosal damage attenuated. Alpha diversity analysis revealed that Huanglian Jiedu Decoction reduced the abundance and diversity of intestinal flora in rats with T2DM; at the phylum level, low-and mediam-dose of Huanglian Jiedu Decoction reduced the abundance of Bacteroidota, Proteobacteria, and Desulfobacterota and increased the abundance of Firmicute and Bacteroidota/Firmicutes, while the high-dose of Huanglian Jiedu Decoction increased the relative abundance of Proteobacteria and Bacteroidota/Firmicutes ratio, and decreaseal the relative; abundance of Firmicute; at the genus level, Huanglian Jiedu Decoction increased the relative abundance of Allobaculum, Blautia, and Lactobacillus; LEfse analysis revealed that the biomarker of low-and medium-dose groups of Huanglian Jiedu Decoction was Lactobacillus, and the structure of the intestinal flora of the low-dose group of Huanglian Jiedu Decoction was highly similar to that of the metformin group. PICRUSt2 function prediction revealed that Huanglian Jiedu Decoction mainly affected carbohydrate and amino acid metabolic pathways. It suggested that Huanglian Jiedu Decoction could reduce fasting blood glucose and increase the number of islet cells in rats with T2DM, and its mechanism of action may be related to increasing the abundance of short-chain fatty acid-producing strains and Lactobacillus and affecting carbohydrate and amino acid metabolic pathways.
Animals ; Drugs, Chinese Herbal/administration & dosage* ; Diabetes Mellitus, Type 2/metabolism* ; Gastrointestinal Microbiome/drug effects* ; Rats ; Male ; Rats, Sprague-Dawley ; Humans ; Bacteria/drug effects* ; Blood Glucose/metabolism*