ABSTRACT
Particulate matter with aerodynamic diameter no larger than 2.5 µm (PM2.5) has been linked to cardiovascular diseases (CVDs) but evidence for vulnerability by sex remains unclear. We performed systematic review and meta-analysis to synthesize the state of scientific evidence on whether cardiovascular risks from PM2.5 differ for men compared to women. The databases Pubmed, Scopus, Embase, and GreenFILE were searched for studies published Jan. 1995 to Feb. 2020. Observational studies conducting subgroup analysis by sex for impacts of short-term or long-term exposure to PM2.5 on target CVDs were included. Data were independently extracted in duplicate and pooled with random-effects meta-regression. Risk ratios (RRs) for long-term exposure and percent changes in outcomes for short-term exposure were calculated per 10 µg/m3 PM2.5 increase. Quality of evidence of risk differences by sex was rated following Grading of Recommendations Assessment, Development and Evaluation (GRADE). A total of 12,502 articles were screened, with 61 meeting inclusion criteria. An additional 32 studies were added from citation chaining. RRs of all CVD mortality for long-term PM2.5 for men and women were the same (1.14; 95% CI: 1.09, 1.22) indicating no statistically different risks. Men and women did not have statistically different risks of daily CVD mortality, hospitalizations from all CVD, ischemic heart disease, cardiac arrest, acute myocardial infarction, and heart failure from short-term PM2.5 exposure (difference in % change in risk per 10 µg/m3 PM2.5: 0.04 (95% CI, -0.42 to 0.51); -0.05 (-0.47 to 0.38); 0.17 (-0.90, 1.24); 1.42 (-1.06, 3.97); 1.33 (-0.05, 2.73); and -0.48 (-1.94, 1.01), respectively). Analysis using GRADE found low or very low quality of evidence for sex differences for PM2.5-CVD risks. In conclusion, this meta-analysis and quality of evidence assessment of current observational studies found very limited evidence of the effect modification by sex for effects of PM2.5 on CVD outcomes in adults, which can inform clinical approaches and policies.
ABSTRACT
BACKGROUND: When anti-tumour therapy is administered to a tumour-host environment, an asymptotic tapering extremity of the tumour cell distribution is noticed. This extremity harbors a small number of residual tumour cells that later lead to secondary malignances. Thus, a method is needed that would enable the malignant population to be completely eliminated within a desired time-frame, negating the possibility of recurrence and drug-induced toxicity. METHODS: In this study, we delineate a computational procedure using the inverse input-reconstruction approach to calculate the unknown drug stimulus input, when one desires a known output tissue-response (full tumour cell elimination, no excess toxicity). The asymptotic extremity is taken care of using a bias shift of tumour-cell distribution and guided control of drug administration, with toxicity limits enforced, during mutually-synchronized chemotherapy (as Temozolomide) and immunotherapy (Interleukin-2 and Cytotoxic T-lymphocyte). RESULTS: Quantitative modeling is done using representative characteristics of rapidly and slowly-growing tumours. Both were fully eliminated within 2 months with checks for recurrence and toxicity over a two-year time-line. The dose-time profile of the therapeutic agents has similar features across tumours: biphasic (lymphocytes), monophasic (chemotherapy) and stationary (interleukin), with terminal pulses of the three agents together ensuring elimination of all malignant cells. The model is then justified with clinical case studies and animal models of different neurooncological tumours like glioma, meningioma and glioblastoma. CONCLUSION: The conflicting oncological objectives of tumour-cell extinction and host protection can be simultaneously accommodated using the techniques of drug input reconstruction by enforcing a bias shift and guided control over the drug dose-time profile. For translational applicability, the procedure can be adapted to accommodate varying patient parameters, and for corrective clinical monitoring, to implement full tumour extinction, while maintaining the health profile of the patient.
