Hejian People's Hospital

The advancement of Maritime Autonomous Surface Ships (MASS) technology is not merely an option but a certainty that will transform the global maritime industry. However, despite offering efficiency, MASS also faces serious security vulnerabilities due to its reliance on complex digital systems, making it susceptible to hybrid threats. Cyberattacks can result in physical damage, economic disruption, and pose a threat to national sovereignty. Analysis indicates that the existing maritime regulatory framework is insufficient to address these challenges. Therefore, Indonesia needs to develop a cybersecurity regulatory model based on four pillars: (1) standardization of secure technology from the design stage; (2) operational regulations and human resource competency development; (3) collaboration in threat information sharing; and (4) law enforcement measures that create a deterrent effect. The implementation of this framework is not only technical but also strategic, aimed at ensuring that Indonesia can leverage autonomous technologies without compromising its security and sovereignty as the World Maritime Axis. By confronting the evolving landscape of cyber threats, Indonesia can transform from a reactive participant into a pioneer in secure and resilient autonomous maritime operations.

This study examines Indonesia’s implementation of white hull diplomacy to manage grey zone dynamics in the North Natuna Sea, positioning the Navy as the strategic enabler behind civilian maritime law-enforcement (Bakamla/Ministry of Marine Affairs and Fisheries). A qualitative literature review of policy documents and accredited academic sources was employed. The analytical framework draws on neorealism (state rationality and self-help), maritime security theory (multidimensional governance of law, economy, defense, and diplomacy), and the nested concepts of maritime diplomacy, defense diplomacy, and their synthesis maritime defense diplomacy emphasizing deterrence without escalation. Findings indicate that the effectiveness of white hull diplomacy depends on a layered defense architecture orchestrated by the Navy: Maritime Domain Awareness for detection and cueing; hydrographic and lawfare support to strengthen legal legitimacy under UNCLOS; and over-the-horizon naval presence to sustain latent deterrence. This “data–enforcement diplomacy” chain validates actions within the EEZ, preserves diplomatic space, reduces escalation risks, and enhances Indonesia’s legal standing. Policy implications include tighter information-operational integration among the Navy–Bakamla–KKP, sustained investment in MDA and evidentiary capacity, and consistent regional/multilateral diplomacy to buttress norms at sea. Accordingly, Indonesia’s maritime strength is assessed by its ability to orchestrate law, diplomacy, and defense rather than by the quantity of grey-hull assets.

As an archipelagic country, Indonesia faces challenges in determining maritime boundaries that have not yet been fully resolved. This uncertainty has led to the emergence of various threats, both traditional and non-traditional in nature. Based on this, various efforts to strengthen national defense have become crucial, including the implementation of the concept of littoral defense. This study employs a descriptive qualitative method to analyze the current situation and Indonesia's readiness to apply the concept of littoral defense. The results indicate that although Indonesia possesses significant defense potential, the integration among the branches of the Indonesian National Armed Forces (TNI) and the development of effective emergency response procedures are key components in the littoral defense concept to safeguard the nation's sovereignty across all borders, including in maritime areas.

The integrated maritime surveillance system in Indonesia is essential for maintaining national sovereignty as the largest archipelagic country in the world. In this context, the roles of the Indonesian Navy, the Indonesian Air Force, and the Indonesian Army are crucial in monitoring vast maritime areas, especially in facing various threats such as smuggling, resource theft, boundary violations, and maritime terrorism. The research method employed is a qualitative approach, utilizing document analysis and direct observation at strategic locations. The findings indicate that despite the availability of various monitoring tools, challenges remain in terms of coverage and surveillance capacity. The synergy among the three branches of the armed forces, along with the development of monitoring technologies and improved communication systems, is key to enhancing the effectiveness of maritime surveillance. By involving the community in surveillance efforts, it is hoped that this system can be more responsive to existing threats, thereby ensuring the sovereignty and maritime security of Indonesia.

The pericapsular nerve group (PENG) block is a regional anaesthesia technique for acute pain management that is becoming frequently employed for emergency lower limb fractures, particularly hip injuries. While current evidence has been predominantly derived from postoperative randomized trials and case series, the results of recent clinical reports support the preprocedural utility of the PENG block in emergency settings for rapid analgesia 40–60% pain score reduction and preservation of motor function. This review synthesizes mechanistic insights and clinical outcomes from the literature, comparing the targeted sensory blockade of the hip capsule with the PENG block with that of systemic opioids (which risks inducing respiratory depression) and fascia iliaca block (which can induce motor impairment). Key advantages of PENG blockade include significant opioid-sparing effects (50–70% reduction morphine use) and almost no motor complications. Standardized ultrasound-guided protocols can address challenges related to anatomical variability. Preliminary evidence from case reports suggests that the efficacy of the PENG block to pelvic and femoral shaft fractures, although multicentre trials are needed to establish optimal doses and long-term functional outcomes. This evidence indicates that PENG blockade could serve as a promising emergency intervention, but further protocol refinement is warranted.

Body mass index (BMI) has a complex association with a variety of chronic pain conditions, which may be influenced by sleep apnea syndrome (SAS). However, the role of SAS within the causal pathway linking BMI to chronic pain remains unconfirmed. This study explored whether and to what extent SAS serves as a mediator between BMI and chronic pain using Bayesian-weighted Mendelian randomization (BWMR) techniques. This study utilized genome-wide association study (GWAS) summary data for BMI (N=461,460) and SAS (N=476,853; based on ICD-10 code diagnostic registries) from the IEU OpenGWAS database, along with chronic pain GWAS data (ICD-10 code-based diagnostic registries) from the FinnGen database. Utilizing BWMR and inverse-variance weighted (IVW) methods, a two-step, two-sample Mendelian randomization (MR) design was employed to investigate the causal relationships between BMI and various types of chronic pain and to assess the mediating role of SAS in the BMI-chronic pain link. Additionally, a suite of sensitivity analyses, including the use of MR-PRESSO to remove outliers, MR-Egger regression to assess horizontal pleiotropy, and Cochran's Q test to evaluate heterogeneity, thereby ensuring the robustness and reliability of the MR study findings. The GWAS data for BMI, SAS, and chronic pain were all derived from European populations, comprising 9,851,867 BMI-associated single-nucleotide polymorphisms (SNPs), 24,183,940 SAS-related SNPs, and 19,680,346 to 19,682,705 chronic pain-linked SNPs in the respective datasets. BWMR revealed significant genetic associations between BMI and various types of chronic pain, including limb pain [odds ratio (OR) =1.34, 95% confidence interval (CI): 1.25-1.44, P<0.001], low back pain (OR =1.34, 95% CI: 1.25-1.43, P<0.001), low back pain with or without sciatica (OR =1.28, 95% CI: 1.21-1.36, P<0.001), and thoracic spine pain (OR =1.18, 95% CI: 1.03-1.36, P=0.02). Additionally, the genetic predisposition of BMI was also strongly associated with the risk of SAS (OR =2.34, 95% CI: 2.12-2.59, P<0.001). Mediation analysis revealed that SAS mediated 15.3% (β=0.045) of BMI's causal effect on limb pain, 26.8% (β=0.078) on low back pain, and 26.8% (β=0.067) on low back pain with or without sciatica. There is a causal relationship between BMI and chronic pain, with SAS acting as a mediator for a portion of the causal effects of BMI on conditions such as limb pain, low back pain, and low back pain with or without sciatica. Therefore, clinical strategies should focus on modulating BMI levels to maintain them within the normal range, which may effectively reduce the incidence risk of chronic pain. Furthermore, in patients with elevated BMI and comorbid SAS, targeted SAS treatment could potentially mitigate BMI-associated chronic pain burden.

Postoperative delirium, a common neurocognitive complication after surgery and anesthesia, requires early detection for potential intervention. Herein, we constructed a multidimensional postoperative delirium risk-prediction model incorporating multiple demographic parameters and blood biomarkers to enhance prediction accuracy. We included 555 patients undergoing radical surgery for colorectal cancer. Demographic characteristics and lipid profiles were collected preoperatively, and perioperative anesthesia and surgical conditions were recorded; blood biomarkers were measured before and after surgery. The 3D-CAM scale was used to assess postoperative delirium occurrence within 3 days after surgery. Patients were divided into the postoperative delirium (N = 100) and non-postoperative delirium (N = 455) groups. Based on machine learning, linear and nine non-linear models were developed and compared to select the optimal model. Shapley value-interpretation methods and mediation analysis were used to assess feature importance and interaction. The median age of the participants was 65 years (interquartile range: 56-71 years; 57.8% male). Among the 10 machine-learning models, the random forest model performed the best (validation cohort, area under the receiver operating characteristic curve of 0.795 [0.704-0.885]). Lipid profile (total cholesterol, triglycerides, and trimethylamine-N-oxide) levels were identified as key postoperative delirium predictors. Mediation analysis further confirmed mediating effects among total cholesterol, trimethylamine-N-oxide, and postoperative delirium; a nomogram model was developed as a web-based tool for external validation and use by other clinicians. Blood biomarkers are crucial in predicting postoperative delirium and aid anesthesiologists in identifying its risks in a timely manner. This model facilitates personalized perioperative management and reduces the occurrence of postoperative delirium. ChiCTR2300075723.