Clinical applications of ginger with an expectation of clinical benefits are receiving significant attention. This systematic review aims to provide a comprehensive discussion in terms of the clinical effects of ginger in all reported areas. Following the preferred reporting items for systematic reviews and meta-analyses (PRISMA) guideline, randomized controlled trials on the effects of ginger were investigated. Accordingly, 109 eligible papers were fully extracted in terms of study design, population characteristics, evaluation systems, adverse effects, and main outcomes. The reporting quality of the included studies was assessed based on the Cochrane Collaboration’s tool for assessing the risk of bias in randomized trials and integrated together with studies that investigated the same subjects. The included studies that examined the improvement of nausea and vomiting in pregnancy, inflammation, metabolic syndromes, digestive function, and colorectal cancer’s markers were consistently supported, whereas other expected functions were relatively controversial. Nevertheless, only 43 clinical trials (39.4%) met the criterion of having a ‘high quality of evidence.’ In addition to the quality assessment result, small populations and unstandardized evaluation systems were the observed shortcomings in ginger clinical trials. Further studies with adequate designs are warranted to validate the reported clinical functions of ginger.

Glucose-6-Phosphate Dehydrogenase (G6PD) deficiency overlaps with malaria endemicity although it predisposes carriers to hemolysis. This fact supports the protection hypothesis against malaria. The aim of this systematic review is to assess the presence and the extent of protective association between G6PD deficiency and malaria. Thirteen databases were searched for papers reporting any G6PD alteration in malaria patients. Twenty-eight of the included 30 studies were eligible for the meta-analysis. Results showed absence of negative association between G6PD deficiency and uncomplicated falciparum malaria (odds ratio (OR), 0.77; 95% confidence interval (CI), 0.59–1.02; p = 0.07). However, this negative association happened in Africa (OR, 0.59; 95% CI, 0.40–0.86; p = 0.007) but not in Asia (OR, 1.24; 95% CI, 0.96–1.61; p = 0.10), and in the heterozygotes (OR, 0.70; 95% CI, 0.57–0.87; p = 0.001) but not the homo/hemizygous (OR, 0.70; 95% CI, 0.46–1.07; p = 0.10). There was no association between G6PD deficiency and total severe malaria (OR, 0.82; 95% CI, 0.61–1.11; p = 0.20). Similarly, there was no association with other malaria species. G6PD deficiency can potentially protect against uncomplicated malaria in African countries, but not severe malaria. Interestingly, this protection was mainly in heterozygous, being x-linked thus related to gender.

Forkhead box (FOX) proteins are multifaceted transcription factors that are significantly implicated in cancer, with various critical roles in biological processes. Herein, we provide an overview of several key members of the FOXA, FOXC, FOXM1, FOXO and FOXP subfamilies. Important pathophysiological processes of FOX transcription factors at multiple levels in a context-dependent manner are discussed. We also specifically summarize some major aspects of FOX transcription factors in association with cancer research such as drug resistance, tumor growth, genomic alterations or drivers of initiation. Finally, we suggest that targeting FOX proteins may be a potential therapeutic strategy to combat cancer.

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Despite the tremendous success, pitfalls have been observed in every step of a clinical metabolomics workflow, which impedes the internal validity of the study. Furthermore, the demand for logistics, instrumentations, and computational resources for metabolic phenotyping studies has far exceeded our expectations. In this conceptual review, we will cover inclusive barriers of a metabolomics-based clinical study and suggest potential solutions in the hope of enhancing study robustness, usability, and transferability. The importance of quality assurance and quality control procedures is discussed, followed by a practical rule containing five phases, including two additional “pre-pre-” and “post-post-” analytical steps. Besides, we will elucidate the potential involvement of machine learning and demonstrate that the need for automated data mining algorithms to improve the quality of future research is undeniable. Consequently, we propose a comprehensive metabolomics framework, along with an appropriate checklist refined from current guidelines and our previously published assessment, in the attempt to accurately translate achievements in metabolomics into clinical and epidemiological research. Furthermore, the integration of multifaceted multi-omics approaches with metabolomics as the pillar member is in urgent need. When combining with other social or nutritional factors, we can gather complete omics profiles for a particular disease. Our discussion reflects the current obstacles and potential solutions toward the progressing trend of utilizing metabolomics in clinical research to create the next-generation healthcare system.