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Sickle cell disease (SCD) is a complex genetic disorder associated with multiple clinical manifestations, including increased susceptibility to bacterial and viral infections. This review article presents a comprehensive analysis of the current literature obtained from various online databases focusing on the relationship between SCD and infections caused by specific pathogens, such as pneumonia- and influenza-causing pathogens, Escherichia coli, Staphylococcus aureus, parvovirus, and hepatitis viruses. We discuss the underlying mechanisms that contribute to the increased susceptibility of individuals with SCD to these infections, primarily related to the pathophysiology of variant hemoglobin (HbSS) and its impact on vascular occlusion, hemolysis, functional asplenia, and immune deficiency. Moreover, we highlight the significant burden of infections on SCD patients, particularly children under five years of age, where they are the leading cause of morbidity and mortality. Additionally, we address the challenges faced in attempts for reducing the global mortality rate associated with SCD, particularly in low-income countries, where factors such as increased pathogen exposure, co-morbidities like malnutrition, lower vaccination rates, and limited healthcare facilities contribute to the high disease burden. This review emphasizes the need for targeted interventions, improved healthcare access, vaccination programs, and infection prevention strategies to alleviate the impact of infections on individuals with SCD and reduce the global mortality rates associated with the disease.

Biohydrogen production from microalgae is a potential alternative energy source that is now intensively being researched. The complex natures of the biological processes involved have afflicted the accuracy of traditional modelling and optimization, besides being costly. Accordingly, machine learning algorithms have been employed to overcome setbacks, as these approaches have the capability to predict nonlinear interactions and handle multivariate data from microalgal biohydrogen studies. Thus, the review focuses on revealing the recent applications of machine learning techniques in microalgal biohydrogen production. The working principles of random forests, artificial neural networks, support vector machines, and regression algorithms are covered. The applications of these techniques are analyzed and compared for their effectiveness, advantages and disadvantages in the relationship studies, classification of results, and prediction of microalgal hydrogen production. These techniques have shown great performance despite limited data sets that are complex and nonlinear. However, the current techniques are still susceptible to overfitting, which could potentially reduce prediction performance. These could be potentially resolved or mitigated by comparing the methods, should the input data be limited.

Hepatotoxicity is a major global public health concern. Despite advances in modern medicine, the demerits of chemically prepared drugs outweigh their merits. In addition, the treatment of liver diseases based on modern medical principles has been found to produce several undesired side effects. Therefore, the exploration of medicinal plants has gained worldwide attention for treating various diseases, including liver diseases, owing to their potential efficacy and cost effectiveness. Several plants, including Andrographis paniculata, Bauhinia purpurea, Commelina nudiflora, Dillenia suffruticosa, Elaeis guineensis, Lygodium microphyllum, and Nephrolepis biserrata, have been reported with hepatoprotection. Moreover, these plants have been shown to play a vital role in ameliorating cellular damage because they contain several phytochemicals, including alkaloids, saponins, flavonoids, tannins, terpenoids, steroids, polyphenols, and diterpenoid lactones. The following antioxidant, anti-inflammatory, immunomodulatory, and hepatoprotective compounds have been found in these plants: andrographolide, rosmarinic acid, phenol, eugenol, 9,12-octadecadienoic, n-hexadecanoic acid, dihydroxy dimethoxy flavone, sitosterol, demethoxycurcumin, quercetin, linoleic acid, stigmasterol, kojic acid, indole-2-one, α-terpinol, linalool, kaempferol, catechin, ellagic acid, and oleanolic acid. This paper aimed to provide an in-depth review of in vivo studies on Malaysian medicinal plants possessing hepatoprotective properties, phytochemical ingredients, and antioxidant mechanisms, with an emphasis on the species proven particularly useful for treating hepatic disorders.

There are no proven prophylactic interventions for COVID-19. We systematically reviewed the efficacy of prophylactic hydroxychloroquine for COVID-19. Studies evaluating hydroxychloroquine for prophylaxis of COVID-19 were searched in several engines until 8 December 2020. Primary outcomes included RT-PCR positivity, COVID-19 infections (positive RT-PCR or compatible COVID-19 symptoms), and all-cause mortality. Random effects meta-analyses were performed for all outcomes. Five randomized controlled trials (RCTs) ( n = 5579) and one cohort ( n = 106) were included. Placebo was the comparator in four RCTs, and usual care in one RCT. Compared to the controls, five RCTs showed that hydroxychloroquine prophylaxis did not reduce RT-PCR positivity (RR 1.01, 95% CI 0.88-1.16), COVID-19 infection (RR 0.98, 95% CI 0.78-1.22), or all-cause mortality (RR 0.73, 95% CI 0.27-1.99). There were no differences of effects by pre- or post-exposure prophylaxis. Prophylaxis with hydroxychloroquine increased the risk of diarrhea, abdominal pain, or vomiting (RR 4.56, 95% CI 1.58-13.19). There were no effects of hydroxychloroquine on other secondary outcomes. Quality of evidence was low to very low for all outcomes. Hydroxychloroquine was not efficacious as a prophylaxis for COVID-19 infections, defined either as RT-PCR positivity or as a composite of RT-PCR positivity or compatible symptoms. Hydroxychloroquine did not reduce all-cause mortality, clinical worsening, or adverse events.

We systematically reviewed the efficacy and safety of hydroxychloroquine as treatment for hospitalized COVID-19. Randomized controlled trials (RCTs) evaluating hydroxychloroquine as treatment for hospitalized COVID-19 patients were searched until 2nd of December 2020. Primary outcomes were all-cause mortality, need of mechanical ventilation, need of non-invasive ventilation, ICU admission and oxygen support at 14 and 30 days. Secondary outcomes were clinical recovery and worsening, discharge, radiological progression of pneumonia, virologic clearance, serious adverse events (SAE) and adverse events. Inverse variance random effects meta-analyses were performed. Thirteen RCTs ( n =18,540) were included. Hydroxychloroquine total doses ranged between 2000 and 12,400 mg; treatment durations were from 5 to 16 days and follow up times between 5 and 30 days. Compared to controls, hydroxychloroquine non-significantly increased mortality at 14 days (RR 1.07, 95%CI 0.92-1.25) or 30 days (RR 1.08, 95%CI 1.00-1.16). Hydroxychloroquine did not affect other primary or secondary outcomes, except SAEs that were significantly higher than the control (RR 1.24, 95%CI 1.05-1.46). Eleven RCTs had high or some concerns of bias. Subgroup analyses were consistent with main analyses. Hydroxychloroquine was not efficacious for treating hospitalized COVID-19 patients and caused more severe adverse events. Hydroxychloroquine should not be recommended as treatment for hospitalized COVID-19 patients.

Comparative efficacy and safety of renal denervation (RDN) interventions for uncontrolled (UH) and resistant hypertension (RH) is unknown. We assessed the comparative efficacy and safety of existing RDN interventions for UH and RH. Six search engines were searched up to 1 May 2020. Primary outcomes were mean 24-h ambulatory and office systolic blood pressure (SBP). Secondary outcomes were mean 24-h ambulatory and office diastolic blood pressure (DBP), clinical outcomes, and serious adverse events. Frequentist random-effects network meta-analyses were used to evaluate effects of RDN interventions. Twenty randomized controlled trials (RCTs) ( n = 2152) were included, 15 in RH ( n = 1544) and five in UH ( n = 608). Intervention arms included radiofrequency (RF) in main renal artery (MRA) ( n = 10), RF in MRA and branches ( n = 4), RF in MRA+ antihypertensive therapy (AHT) ( n = 5), ultrasound (US) in MRA ( n = 3), sham ( n = 8), and AHT ( n = 9). RF in MRA and branches ranked as the best treatment to reduce 24-h ambulatory, daytime, and nighttime SBP and DBP versus other interventions (p-scores: 0.83 to 0.97); significant blood pressure effects were found versus sham or AHT. RF in MRA+AHT was the best treatment to reduce office SBP and DBP (p-scores: 0.84 and 0.90, respectively). RF in MRA and branches was the most efficacious versus other interventions to reduce 24-h ambulatory SBP and DBP in UH or RH.