We report a case of renal tubular acidosis (RTA) in a patient with HIV infection and AIDS. A 33-year-old HIV-positive man with Hepatitis C and tuberculous lymphadenitis was admitted due to deep venous thrombosis and generalized muscle weakness. He had never received anti-retroviral medication. The blood gases and serum electrolytes showed hyperchloremic normal anion gap metabolic acidosis with severe hypokalemia and alkaline urine. Diagnosis of distal RTA was made. His renal function and serum globulin level remained within normal range throughout his illness. Clinicians should be alert to renal tubular disorders in HIV/AIDS patients even in the absence of anti-retroviral therapy or hypergammaglobulinemic state.
Kimura's disease is a rare condition and typically presents as non-tender subcutaneous swellings in the head and neck region, usually in the pre-auricular and submandibular areas. It is associated with lymphadenopathy (both local and distal), marked peripheral eosinophilia, and an elevated IgE level. It can easily be mistaken for a malignant disorder. Fine needle aspiration can be misleading, and a diagnosis is established only by histopathological examination. Renal involvement, which may affect up to 60% of patients, is the only systemic manifestation. We report a case of Kimura's disease in a Malay patient who was associated with steroid-responsive nephrotic syndrome.
Metabolic engineering is defined as improving the cellular activities of an organism by manipulating the metabolic, signal or regulatory network. In silico reaction knockout simulation is one of the techniques applied to analyse the effects of genetic perturbations on metabolite production. Many methods consider growth coupling as the objective function, whereby it searches for mutants that maximise the growth and production rate. However, the final goal is to increase the production rate. Furthermore, they produce one single solution, though in reality, cells do not focus on one objective and they need to consider various different competing objectives. In this work, a method, termed ndsDSAFBA (non-dominated sorting Differential Search Algorithm and Flux Balance Analysis), has been developed to find the reaction knockouts involved in maximising the production rate and growth rate of the mutant, by incorporating Pareto dominance concepts. The proposed ndsDSAFBA method was validated using three genome-scale metabolic models. We obtained a set of non-dominated solutions, with each solution representing a different mutant strain. The results obtained were compared with the single objective optimisation (SOO) and multi-objective optimisation (MOO) methods. The results demonstrate that ndsDSAFBA is better than the other methods in terms of production rate and growth rate.