The Internet of Healthcare Things (IoHT) is an essential IoT domain that encompasses the necessary capabilities to transform the current healthcare system. IoHT generates, transfers, manages, stores, and processes highly confidential medical data and sensitive personal information. Thus, IoHT is a critical application from a security perspective and is most favorably targeted by attackers. Several security-breaching attempts can be carried out due to the vulnerabilities of the IoHT that put classified data at constant risk. Henceforth, this work aims to inspect the performance of 6LoWPAN-RPL-based `Patient-Centric IoHT’ in the presence of malicious intruders conducting blackhole, rank, and DoDAG attacks in both normal and emergency operational modes of the mentioned resource-constraint network. PC-IoHT is simulated on the Cooja simulator and Contiki-OS for each attack with two and four intruders (out of 10 motes) for both operation modes. Several performance evaluation parameters are used to assess the overall performance of the considered PC-IoHT. The attacks’ impact on PC-IoHT is analyzed by comparing blackhole, rank, and DoDAG attacks with the no-attack scenario.

Duchenne muscular dystrophy (DMD) is a fatal X-linked recessive neuromuscular disease prevalent in 1 in 3500 to 5000 males worldwide. As a result of mutations that interrupt the reading frame of the dystrophin gene (DMD), DMD is characterized by a loss of dystrophin protein which leads to decreased muscle membrane integrity, which increases susceptibility to degeneration. CRISPR/Cas9 technology has garnered interest as an avenue for DMD therapy due to its potential for permanent exon skipping, which can restore the disrupted DMD reading frame in DMD and lead to dystrophin restoration. An RNA-guided DNA endonuclease system, CRISPR/Cas9 allows for the targeted editing of specific sequences in the genome. The efficacy and safety of CRISPR/Cas9 as a therapy for DMD has been evaluated by numerous studies in vitro and in vivo, with varying rates of success. Despite the potential of CRISPR/Cas9-mediated gene editing for the long-term treatment of DMD, its translation into the clinic is currently challenged by issues such as off-targeting, immune response activation, and sub-optimal in vivo delivery. Its nature as being mostly a personalized form of therapy also limits applicability to DMD patients, who exhibit a wide spectrum of mutations. This review summarizes the various CRISPR/Cas9 strategies that have been tested in vitro and in vivo for the treatment of DMD. Perspectives on the approach will be provided, and the challenges faced by CRISPR/Cas9 in its road to the clinic will be briefly discussed.

Objective: The primary objective of this study was to develop a logistic regression model to predict post-operative in-hospital mortality rates for patients undergoing emergency cardiac surgeries, with the aim of improving predictive accuracy over traditional risk assessment tools and enhancing patient outcomes and clinical decision-making. Methods: Data were collected from 4,855 patients who underwent emergency cardiac surgeries at a tertiary hospital between 2008 and 2017. The analysis incorporated demographic, anthropomet- ric, and clinical factors, including the ASA classification, emergency status, and various preoperative laboratory values. A logistic regression model was developed, and the Elixhauser Comorbidity Index was calculated using standard ICD-10 codes for its comprehensive assessment of comorbidities. Model performance was evaluated using metrics such as AUROC, AUPRC, accuracy, precision, recall, and F1 score. Results: The logistic regression model demonstrated strong predictive performance, with an AUROC of 0.939 and an AUPRC of 0.350. Key pre-operative factors identified included emergency operation status, ASA classification, and preoperative prothrombin time. The model significantly outperformed the traditional ASA classification system, which showed an AUROC of 0.524 and an AUPRC of 0.010. These findings suggest a substantial improvement in predicting post-operative mortality. Conclusion: The logistic regression model significantly improves the prediction of post-operative mortality in emergency cardiac surgeries compared to the ASA classification system. These findings highlight the potential of incorporating comprehensive pre-operative factors into predictive models to enhance clinical decision-making and patient outcomes. Implementing such models in routine clinical practice could lead to more accurate risk assessments, better resource allocation, and improved patient care.

While paresthesia-based spinal cord stimulation (SCS) has been proven effective to treat chronic neuropathic pain, initial benefits may lead to the development of “Failed SCS Syndrome’ (FSCSS) defined as decrease over time related to Loss of Efficacy (LoE) with or without Loss of Coverage (LoC). Development of technologies associating new paresthesia-free stimulation waveforms and implanted pulse generator adapters provide opportunities to manage patients with LoE. The main goal of our study was to investigate salvage procedures, through neu-rostimulation adapters, in patients already implanted with SCS and experienced LoE. We retro-spectively analyzed a cohort of patients who were offered new SCS programs/waveforms through an implanted adapter between 2018 and 2021. Patients were evaluated before, and at 1, 3, 6 and 12-month follow-up. Outcomes included pain intensity rating with Visual Analog Scale (VAS), pain/coverage mappings and stimulation preferences. Last follow-up evaluations (N=27) showed significant improvement in VAS (p = 0.0001), ODI (p = 0.021) and Quality of Life (p=0.023). In the 11/27 patients with LoC, SCS efficacy on pain intensity (36.89%) was accompa-nied by paresthesia coverage recovery (55.57%) and pain surface decrease (47.01%). At 12-month follow-up, 81.3% preferred to keep tonic stimulation in their waveform portfolio. SCS conver-sion using adapters appears promising as a salvage solution, with an emphasis on paresthesia recapturing enabled by spatial retargeting. In light of these results, adapters could be integrated to SCS rescue algorithms or should be considered in SCS rescue.