Misurata University

Cytokines play critical roles in regulating interactions between pancreatic beta cells and immune cells in the development of type 1 diabetes. It has been shown that pro-inflammatory cytokines released during the disease can exacerbate the disease, while anti-inflammatory cytokines provide protection. This study aimed to evaluate IL-6 and IL-4 levels in the serum of children with type 1 diabetes and compare them to healthy controls. Seventy children with type 1 diabetes and 33 children without diabetes were recruited between September and December 2024. Serum levels of interleukin-6 and interleukin-4 were measured using an ELISA test. The results of this study showed a higher mean IL-6 concentration in patients (12.95±0.83) compared to healthy controls (2.62±0.33), with a significant difference (p=0.001). The average IL-4 concentration in healthy controls was higher (41.77±13.34) compared to healthy controls (18.71±7.08), but without a significant difference (p=0.10). The study also showed significant differences in IL-6 and IL-4 concentrations in children with type 1 diabetes and the duration of the disease. There was a positive relationship between IL-6 concentrations and cumulative blood sugar, body mass index, and fasting blood sugar. No significant differences were found in IL-6 levels between males and females with diabetes. Conclusion: The evidence from this study supports the possibility of a chronic inflammatory state in children with type 1 diabetes, as evidenced by elevated serum IL-6 levels. The longer the disease lasts, the more severe the effects become, potentially leading to microvascular disorders, eye problems, and kidney problems.

Urinary tract infections (UTIs) caused by Escherichia coli remain a major global health burden, particularly among diabetic patients who are prone to recurrent and complicated infections. This article determines the prevalence, antimicrobial resistance patterns, and clinical predictors of extended-spectrum β-lactamase (ESBL) and AmpC β-lactamase coproduction among uropathogenic E. coli isolates. Cross-sectional study was conducted on 300 adult patients with culture-confirmed E. coli UTIs at Misurata Medical Center, including 150 people living with diabetes (PLWD) and 150 nondiabetic participants. Midstream urine specimens were collected and cultured on standard media. Antimicrobial susceptibility testing followed the Clinical and Laboratory Standards Institute 2024 guidelines, while ESBL and AmpC β-lactamases were phenotypically detected using the double-disk synergy and inhibitor-based disk tests. Data were analyzed using SPSS v27 and R v4.3.2. Categorical and continuous variables were compared using chi-square/Fisher's exact and Mann–Whitney U tests, respectively. Predictors of coproduction and its impact on treatment failure were identified via multivariate logistic regression; a p-value of < 0.05 was considered statistically significant. The total prevalence of ESBL, AmpC, and ESBL + AmpC coproduction was 58.3, 14.3, and 14.0%, respectively. While the prevalence of ESBL-only and AmpC-only phenotypes did not differ significantly between PLWD and nondiabetic patients, coproduction was significantly higher in PLWD (22%) compared with nondiabetic patients (6%; p < 0.001) and was associated with extensive multidrug resistance (93%). Diabetes mellitus (adjusted odds ratio [OR] = 3.64; p = 0.001) and prior antibiotic exposure (adjusted OR = 2.18; p = 0.041) were independent predictors of coproduction. ESBL + AmpC coproduction in uropathogenic E. coli represents an emerging therapeutic and epidemiological concern, particularly among PLWD. Routine AmpC screening and rational antibiotic policies are urgently required to mitigate treatment failure and limit resistance.

Perkembangan media sosial telah mengubah cara perusahaan ritel membangun hubungan dengan konsumen. Instagram menjadi salah satu platform yang banyak dimanfaatkan karena kekuatan visual dan interaktivitasnya dalam menyampaikan pesan merek. Penelitian ini bertujuan untuk menganalisis strategi konten media sosial yang digunakan oleh Guardian Indonesia dalam membangun brand engagement di Instagram. Metode penelitian yang digunakan adalah pendekatan kualitatif deskriptif dengan teknik analisis isi (content analysis). Data penelitian diperoleh dari 20 unggahan akun resmi Instagram @guardian_id selama periode Oktober–November 2025. Analisis difokuskan pada jenis konten, bentuk penyajian pesan, unsur visual dan teks, serta interaksi audiens. Penelitian ini diharapkan dapat memberikan gambaran mengenai pola strategi konten yang diterapkan Guardian Indonesia dalam meningkatkan keterlibatan merek serta menjadi referensi bagi pengembangan strategi komunikasi digital dalam manajemen ritel.

Background: In trauma cases, genitourinary tract injuries occur in approximately 10% of cases, with renal trauma being the most common. Management of blunt renal trauma has evolved from operative to non-operative approaches over the last 30 years. Materials and Methods: This retrospective study evaluated the efficacy of non-operative management (NOM) for high-grade blunt renal trauma at Misurata Medical Center, Libya, from January 2016 to January 2018. Sixty-seven male patients (ages 25-67) were included. Results: The primary mechanisms of injury were road traffic accidents (52%), falls (28%), and fighting (20%), with most non-MVA injuries occurring during the 2016 war. The right kidney was more frequently affected (61%). The majority of injuries were Grade III and IV lacerations. Eighty-seven percent of patients presented with associated abdominal organ injuries. Two patients with Grade V injuries, who were hemodynamically unstable with active bleeding and associated liver trauma, underwent immediate nephrectomy. Crucially, the study found that renal injury grade was not a statistically significant predictor for operative management in hemodynamically stable patients. Short-term complications included urinary tract infections, hematuria, and abscesses. Mortality was not significant for stable patients. Conclusion: This study supports the increasing trend towards conservative management, demonstrating that NOM is largely successful for high-grade blunt renal trauma in hemodynamically stable patients, with a low failure rate and excellent renal salvage.

This paper proposes a technical model using artificial intelligence to analyze and transform negative behaviors (e.g., selfishness, information hoarding) into positive ones (e.g., collaboration, knowledge sharing) within public institutions. The system integrates Social Network Analysis (SNA), Reinforcement Learning (RL), and Natural Language Processing (NLP). Developed with data from Libyan healthcare institutions, preliminary results suggest a potential 60% reduction in negative behaviors and a 75% increase in collaborative engagement within six months. Keywords: Behavioral Engineering; Ethical AI; Social Network Analysis; Reinforcement Learning; Public Institutions

ABSTRACT Robust random number generation is critical in cryptographic systems and secure applications, where unpredictability, uniformity, and entropy quality directly impact system resilience. This paper introduces the Entropy Mixing Network (EMN), a hybrid random number generator that combines deterministic pseudo‐random generation with dynamic entropy injection, with the aim to reinforce randomness under adversarial or entropy‐constrained conditions. We present a comprehensive evaluation framework incorporating statistical metrics, spectral and temporal analyses, and cryptographic benchmarks. EMN is tested against established generators such as Python's SystemRandom and MersenneTwister , as well as cryptographic standards including AES‐CTR and ChaCha20. Notably, EMN achieves the highest Chi‐squared p ‐value (0.9430), maximum entropy (7.9840), and lowest predictability (−0.0286) in core tests, confirming its statistical robustness. Extensive Dieharder benchmarking further positions EMN as competitive with state‐of‐the‐art cryptographic generators, despite a moderate increase in computation time (0.2602 s per million 256‐bit outputs). These findings suggest EMN is well‐suited for secure key generation, session entropy provisioning, and other cryptographic tasks where randomness quality is paramount.

This study assessed heavy metal (cadmium, lead, and arsenic) contamination in fish, algae, and seawater samples from the coast of Zawiya, Libya. Concentrations were determined using Atomic Absorption Spectrophotometry (AAS) after appropriate sample digestion. Results showed that all metal concentrations in fish and seawater were below detection limits, indicating they are currently safe for human consumption and the environment. In contrast, certain marine organisms demonstrated a significant capacity for bioaccumulation of these metals. A sample of seaweed (Posidonia oceanica) showed a cadmium concentration of 9.6 mg/kg, which exceeded the internationally permissible limit of 5.5 mg/kg. Similarly, brown algae accumulated a high concentration of arsenic (26.6 mg/kg), highlighting its role as a biomonitor. These findings underscore the importance of using algae and seagrasses as effective bioindicators for monitoring heavy metal pollution in coastal ecosystems, even when contamination is not evident in fish or water.