METHODS: Forty-one healthy sedentary males were recruited and randomised into four groups: sedentary control with placebo (C), probiotics (P), circuit training with placebo (Ex), and circuit training with probiotics (PEx) groups. Participants in the Ex and PEx groups performed a progressive load of circuit training at 3 times/week for 12 weeks. Each circuit comprised 10 exercises with work to rest ratio of 1:2. Participants consumed either multi-strain probiotics or placebo twice daily for 12 weeks. Body height and weight, blood pressure, resting heart rate, saliva and blood samples were collected at pre- and post-tests.
RESULTS: Saliva flow rate and salivary IgA, α-amylase, lactoferrin and lysozyme responses were not significantly different (P>0.05) between groups and also between pre- and post-test within each group. Similarly, total leukocytes, total lymphocytes, T lymphocytes, T-helper, T-cytotoxic, B lymphocytes, and natural killer cells counts were not significantly affected (P>0.05) by the probiotics and/or circuit training. However, circuit training significantly increased (P<0.05) immune cells count at post-test as compared to pre-test. Yet, a combination of circuit training and probiotics showed no significant (P>0.05) effects on immune cells count.
CONCLUSIONS: This study did not provide enough support for the positive effects of probiotics on immune responses among sedentary young males following resistance exercise. However, 12 weeks of circuit training enhanced immune cells count.
METHODS: From bioinformatics data, mismatched mouse amino acids in variable light and heavy chain amphipathic regions were identified and substituted with those common to human antibody framework. Appropriate synthetic DNA sequences inserted into vectors were transfected into HEK293 cells to produce the humanized antibody.
RESULTS: Humanized antibodies showed specific binding to CD20 and greater cytotoxicity to cancer WIL2-NS cell proliferation than rituximab in vitro.
CONCLUSION: A humanized version of rituximab with potential to be developed into a biobetter for treatment of B-cell disorders has been successfully generated using a logical and bioinformatics approach.
OBJECTIVES: We sought to define the clinical features that distinguish DOCK8 deficiency from other forms of HIES and CIDs, study the mutational spectrum of DOCK8 deficiency, and report on the frequency of specific clinical findings.
METHODS: Eighty-two patients from 60 families with CID and the phenotype of AR-HIES with (64 patients) and without (18 patients) DOCK8 mutations were studied. Support vector machines were used to compare clinical data from 35 patients with DOCK8 deficiency with those from 10 patients with AR-HIES without a DOCK8 mutation and 64 patients with signal transducer and activator of transcription 3 (STAT3) mutations.
RESULTS: DOCK8-deficient patients had median IgE levels of 5201 IU, high eosinophil levels of usually at least 800/μL (92% of patients), and low IgM levels (62%). About 20% of patients were lymphopenic, mainly because of low CD4(+) and CD8(+) T-cell counts. Fewer than half of the patients tested produced normal specific antibody responses to recall antigens. Bacterial (84%), viral (78%), and fungal (70%) infections were frequently observed. Skin abscesses (60%) and allergies (73%) were common clinical problems. In contrast to STAT3 deficiency, there were few pneumatoceles, bone fractures, and teething problems. Mortality was high (34%). A combination of 5 clinical features was helpful in distinguishing patients with DOCK8 mutations from those with STAT3 mutations.
CONCLUSIONS: DOCK8 deficiency is likely in patients with severe viral infections, allergies, and/or low IgM levels who have a diagnosis of HIES plus hypereosinophilia and upper respiratory tract infections in the absence of parenchymal lung abnormalities, retained primary teeth, and minimal trauma fractures.