Drug-induced erectile dysfunction: a real-world pharmacovigilance study using the FDA adverse event reporting system database.

BACKGROUND: The comprehensive quantitative and comparative risk data of drug-induced erectile dysfunction (ED) are still lacking, and this study aims to supplement this information. RESEARCH DESIGN AND METHODS: We reviewed all the ED reports in the FDA Adverse Event Reporting System (FAERS) database from 2004 to 2023 and summarized a potential ED culprit-drug list and its corresponding reporting frequency. The reporting odd ratio (ROR) method was used to conduct disproportionality analysis. RESULTS: 20,098 ED reports were retrieved from the FAERS database, which recorded 734 different ED culprit-drugs, involving 74 drug classes. Finasteride was the drug with the highest reporting frequency, and urologicals was the drug class with the highest reporting frequency. In disproportionality analysis, 209 drugs with positive signals showed a close relationship with ED occurrence, among which finasteride was the drug with the highest signal strength. Among 209 drugs with positive signals, 27 were compound preparations, and the risk level of compound preparations was usually higher than their single active ingredient. CONCLUSIONS: Our study integrated quantitative and comparative ED risk data of 734 drugs by using the FAERS database, which can provide reference information for regulators, medical personnel, and others involved in drug management and use.

Homotypic cell-in-cell structure as a novel prognostic predictor in non-small cell lung cancer and frequently localized at the invasive front.

Homotypic cell-in-cell structures (hoCICs) are associated with tumor proliferation, invasion, and metastasis and is considered a promising prognostic marker in various cancers. However, the role of hoCICs in non-small cell lung cancer (NSCLC) remains unclear. Tumor tissue sections were obtained from 411 NSCLC patients. We analyzed the relationship between clinicopathological variables and the number of hoCICs. LASSO and multivariate Cox regression analysis were employed to identify prognostic factors for NSCLC. The impact of hoCICs on overall survival (OS) and disease-free survival (DFS) was assessed using the Kaplan-Meier curves and log-rank test. Prognostic models for OS and DFS were developed and validated using the C-index, time-dependent area under the curve (AUC), net reclassification improvement (NRI), integrated discrimination improvement (IDI), calibration curves and decision curve analysis (DCA). Among the cohort, 56% of patients had hoCICs while 44% did not. Notably, hoCICs were primarily found at the tumor invasion front. Male gender, smoking, squamous cell carcinoma, low differentiation, tumor size ≥ 3 cm, advanced TNM stage, lymph node metastasis, pleural invasion, vascular invasion, necrosis, P53 mutation, and high expression of Ki-67 were identified as relative risk factors for hoCICs. Furthermore, hoCICs was found to be a significant prognostic factor for both OS and DFS, with higher frequencies of hoCICs correlating with poorer outcomes. We constructed nomograms for predicting 1-, 3-, and 5-year OS and DFS based on hoCICs, and the calibration curves showed good agreement between the predicted and actual outcomes. The results of the C-index, time-dependent AUC, NRI, IDI, and DCA analyses demonstrated that incorporating hoCICs into the prognostic model significantly enhanced its predictive power and clinical applicability. HoCICs indicated independent perdictive value for OS and DFS in patients with NSCLC. Furthermore, the frequent localization of hoCICs at the tumor invasion front suggested a strong association between hoCICs and tumor invasion as well as metastasis.

Real-time IMU-Based Kinematics in the Presence of Wireless Data Drop.

Wireless inertial motion capture holds promise for real-time human-machine interfaces and home-based rehabilitation applications. However, wireless data drop can cause significant estimation errors deteriorating performance or even making the system unusable. It is currently unclear how to estimate non-periodic kinematics with wearable inertial measurement units (IMUs) in the presence of wireless data drop (packet loss). We thus propose a novel inference encoder-decoder network model for real-time kinematics during dynamic movement. Twenty-four healthy subjects performed yoga, golf, swimming, dance, and badminton movement activities while wearing IMUs and 10-90% of each IMU's data were randomly removed to determine the effects of data drop on estimation accuracy with and without the proposed model. Results demonstrated a reduction in RMSE of 45.2% to 51.5% in the upper limb kinematic estimation of the proposed model compared to the No Prediction strategy, and a reduction of 19.1% to 31.3% of the proposed model compared with an baseline LSTM model. In addition, the proposed model has significantly less error (p<0.05) than the No Prediction strategy and the baseline LSTM model for 10%, 20%, 30%, 40%, 50%, 60%, 70%, and 80% data drop. These results could enable wearable, wireless IMU dynamic motion analysis and assessment with reduced kinematic estimation error in the presence of varying amounts of wireless data drop and thus could further facilitate human-machine interaction and home-based medical assessment and treatment.

Automated, IMU-based spine angle estimation and IMU location identification for telerehabilitation.

BACKGROUND: Telerehabilitation is a promising avenue for improving patient outcomes and expanding accessibility. However, there is currently no spine-related assessment for telerehabilitation that covers multiple exercises. METHODS: We propose a wearable system with two inertial measurement units (IMUs) to identify IMU locations and estimate spine angles for ten commonly prescribed spinal degeneration rehabilitation exercises (supine chin tuck head lift rotation, dead bug unilateral isometric hold, pilates saw, catcow full spine, wall angel, quadruped neck flexion/extension, adductor open book, side plank hip dip, bird dog hip spinal flexion, and windmill single leg). Twelve healthy subjects performed these spine-related exercises, and wearable IMU data were collected for spine angle estimation and IMU location identification. RESULTS: Results demonstrated average mean absolute spinal angle estimation errors of 2.59 ∘ and average classification accuracy of 92.97%. The proposed system effectively identified IMU locations and assessed spine-related rehabilitation exercises while demonstrating robustness to individual differences and exercise variations. CONCLUSION: This inexpensive, convenient, and user-friendly approach to spine degeneration rehabilitation could potentially be implemented at home or provide remote assessment, offering a promising avenue to enhance patient outcomes and improve accessibility for spine-related rehabilitation. TRIAL REGISTRATION:  No. E2021013P in Shanghai Jiao Tong University.

Ferroptosis and hepatocellular carcinoma: the emerging role of lncRNAs.

Hepatocellular carcinoma is the most common form of primary liver cancer and poses a significant challenge to the medical community because of its high mortality rate. In recent years, ferroptosis, a unique form of cell death, has garnered widespread attention. Ferroptosis, which is characterized by iron-dependent lipid peroxidation and mitochondrial alterations, is closely associated with the pathological processes of various diseases, including hepatocellular carcinoma. Long non-coding RNAs (lncRNAs), are a type of functional RNA, and play crucial regulatory roles in a variety of biological processes. In this manuscript, we review the regulatory roles of lncRNAs in the key aspects of ferroptosis, and summarize the research progress on ferroptosis-related lncRNAs in hepatocellular carcinoma.

Radiotherapy activates picolinium prodrugs in tumours.

Radiotherapy-induced prodrug activation provides an ideal solution to reduce the systemic toxicity of chemotherapy in cancer therapy, but the scope of the radiation-activated protecting groups is limited. Here we present that the well-established photoinduced electron transfer chemistry may pave the way for developing versatile radiation-removable protecting groups. Using a functional reporter assay, N-alkyl-4-picolinium (NAP) was identified as a caging group that efficiently responds to radiation by releasing a client molecule. When evaluated in a competition experiment, the NAP moiety is more efficient than other radiation-removable protecting groups discovered so far. Leveraging this property, we developed a NAP-derived carbamate linker that releases fluorophores and toxins on radiation, which we incorporated into antibody-drug conjugates (ADCs). These designed ADCs were active in living cells and tumour-bearing mice, highlighting the potential to use such a radiation-removable protecting group for the development of next-generation ADCs with improved stability and therapeutic effects.

Graph-Driven Simultaneous and Proportional Estimation of Wrist Angle and Grasp Force via High-Density EMG.

Myoelectric prostheses are generally unable to accurately control the position and force simultaneously, prohibiting natural and intuitive human-machine interaction. This issue is attributed to the limitations of myoelectric interfaces in effectively decoding multi-degree-of-freedom (multi-DoF) kinematic and kinetic information. We thus propose a novel multi-task, spatial-temporal model driven by graphical high-density electromyography (HD-EMG) for simultaneous and proportional control of wrist angle and grasp force. Twelve subjects were recruited to perform three multi-DoF movements, including wrist pronation/supination, wrist flexion/extension, and wrist abduction/adduction while varying grasp force. Experimental results demonstrated that the proposed model outperformed five baseline models, with the normalized root mean square error of 13.2% and 9.7% and the correlation coefficient of 89.6% and 91.9% for wrist angle and grasp force estimation, respectively. In addition, the proposed model still maintained comparable accuracy even with a significant reduction in the number of HD-EMG electrodes. To the best of our knowledge, this is the first study to achieve simultaneous and proportional wrist angle and grasp force control via HD-EMG and has the potential to empower prostheses users to perform a broader range of tasks with greater precision and control, ultimately enhancing their independence and quality of life.

3D Knee and Hip Angle Estimation With Reduced Wearable IMUs via Transfer Learning During Yoga, Golf, Swimming, Badminton, and Dance.

Wearable lower-limb joint angle estimation using a reduced inertial measurement unit (IMU) sensor set could enable quick, economical sports injury risk assessment and motion capture; however the vast majority of existing research requires a full IMU set attached to every related body segment and is implemented in only a single movement, typically walking. We thus implemented 3-dimensional knee and hip angle estimation with a reduced IMU sensor set during yoga, golf, swimming (simulated lower body swimming in a seated posture), badminton, and dance movements. Additionally, current deep-learning models undergo an accuracy drop when tested with new and unseen activities, which necessitates collecting large amounts of data for the new activity. However, collecting large datasets for every new activity is time-consuming and expensive. Thus, a transfer learning (TL) approach with long short-term memory neural networks was proposed to enhance the model's generalization ability towards new activities while minimizing the need for a large new-activity dataset. This approach could transfer the generic knowledge acquired from training the model in the source-activity domain to the target-activity domain. The maximum improvement in estimation accuracy (RMSE) achieved by TL is 23.6 degrees for knee flexion/extension and 22.2 degrees for hip flexion/extension compared to without TL. These results extend the application of motion capture with reduced sensor configurations to a broader range of activities relevant to injury prevention and sports training. Moreover, they enhance the capacity of data-driven models in scenarios where acquiring a substantial amount of training data is challenging.

Nucleation Domains in Biomineralization: Biomolecular Sequence and Conformational Features.

Biomolecules play a vital role in the regulation of biomineralization. However, the characteristics of practical nucleation domains are still sketchy. Herein, the effects of the representative biomolecular sequence and conformations on calcium phosphate (Ca-P) nucleation and mineralization are investigated. The results of computer simulations and experiments prove that the line in the arrangement of dual acidic/essential amino acids with a single interval (Bc (Basic) -N (Neutral) -Bc-N-Ac (Acidic)- NN-Ac-N) is most conducive to the nucleation. 2α-helix conformation can best induce Ca-P ion cluster formation and nucleation. "Ac- × × × -Bc" sequences with α-helix are found to be the features of efficient nucleation domains, in which process, molecular recognition plays a non-negligible role. It further indicates that the sequence determines the potential of nucleation/mineralization of biomolecules, and conformation determines the ability of that during functional execution. The findings will guide the synthesis of biomimetic mineralized materials with improved performance for bone repair.

Drug-induced QT prolongation and torsade de pointes: a real-world pharmacovigilance study using the FDA Adverse Event Reporting System database.

Introduction: Drug-induced QT prolongation and (or) Torsade de Pointes (TdP) is a well-known serious adverse reaction (ADR) for some drugs, but the widely recognized comprehensive landscape of culprit-drug of QT prolongation and TdP is currently lacking. Aim: To identify the top drugs reported in association with QT prolongation and TdP and provide information for clinical practice. Method: We reviewed the reports related to QT prolongation and TdP in the FDA Adverse Event Reporting System (FAERS) database from January 1, 2004 to December 31, 2022, and summarized a potential causative drug list accordingly. Based on this drug list, the most frequently reported causative drugs and drug classes of QT prolongation and TdP were counted, and the disproportionality analysis for all the drugs was conducted to in detect ADR signal. Furthermore, according to the positive-negative distribution of ADR signal, we integrated the risk characteristic of QT prolongation and TdP in different drugs and drug class. Results: A total of 42,713 reports in FAERS database were considered to be associated with QT prolongation and TdP from 2004 to 2022, in which 1,088 drugs were reported as potential culprit-drugs, and the largest number of drugs belonged to antineoplastics. On the whole, furosemide was the most frequently reported drugs followed by acetylsalicylic acid, quetiapine, citalopram, metoprolol. In terms of drug classes, psycholeptics was the most frequently reported drug classes followed by psychoanaleptics, analgesics, beta blocking agents, drugs for acid related disorders. In disproportionality analysis, 612 drugs showed at least one positive ADR signals, while citalopram, ondansetron, escitalopram, loperamide, and promethazine were the drug with the maximum number of positive ADR signals. However, the positive-negative distribution of ADR signals between different drug classes showed great differences, representing the overall risk difference of different drug classes. Conclusion: Our study provided a real-world overview of QT prolongation and TdP to drugs, and the presentation of the potential culprit-drug list, the proportion of reports, the detection results of ADR signals, and the distribution characteristics of ADR signals may help understand the safety profile of drugs and optimize clinical practice.