Simplified within-host and Dose-response Models of SARS-CoV-2.

Understanding the mechanistic dynamics of transmission is key to designing more targeted and effective interventions to limit the spread of infectious diseases. A well-described within-host model allows explicit simulation of how infectiousness changes over time at an individual level. This can then be coupled with dose-response models to investigate the impact of timing on transmission. We collected and compared a range of within-host models used in previous studies and identified a minimally-complex model that provides suitable within-host dynamics while keeping a reduced number of parameters to allow inference and limit unidentifiability issues. Furthermore, non-dimensionalised models were developed to further overcome the uncertainty in estimates of the size of the susceptible cell population, a common problem in many of these approaches. We will discuss these models, and their fit to data from the human challenge study (see Killingley et al. (2022)) for SARS-CoV-2 and the model selection results, which has been performed using ABC-SMC. The parameter posteriors have then used to simulate viral-load based infectiousness profiles via a range of dose-response models, which illustrate the large variability of the periods of infection window observed for COVID-19.

A meta-analysis of the effect and safety of platinum-based neoadjuvant chemotherapy in treatment of resectable triple-negative breast cancer.

Triple-negative breast cancer (TNBC) is the most aggressive and fatal subtype of breast cancer. The effectiveness of platinum-based neoadjuvant chemotherapy in treatment of cancer has many divergent opinions. A search was conducted in the PubMed, EBSCO, Web of Science and Cochrane Library databases for relevant studies published before August 2020. The primary endpoint was pathological complete response (pCR) while the secondary endpoints were objective response rate (ORR), overall survival (OS) and progression-free survival (PFS). Nine randomized controlled trials comprised of 1873 patients were included in this meta-analysis. Platinum-based neoadjuvant chemotherapy showed significant improvements in pCR (RR = 1.51, 95% CI, 1.25-1.82, P < 0.001), ORR (RR = 1.20, 95% CI, 1.07-1.34, P = 0.001), OS (HR=0.56; 95% CI, 0.15-0.96, P < 0.001) and PFS (HR = 0.48, 95% CI, 0.22-0.73, P < 0.001) compared to nonplatinum neoadjuvant chemotherapy. Moreover, addition of platinum compounds did not significantly increase the side effects of any grade. However, there was an increase in blood toxicity of grade 3 patients which meant that it was mainly confined to the bone marrow/blood system. Platinum-based neoadjuvant chemotherapy can safely improve short-term and long-term outcomes in resectable TNBC patients.

Single-cell biclustering for cell-specific transcriptomic perturbation detection in AD progression.

The pathogenesis of Alzheimer disease (AD) involves complex gene regulatory changes across different cell types. To help decipher this complexity, we introduce single-cell Bayesian biclustering (scBC), a framework for identifying cell-specific gene network biomarkers in scRNA and snRNA-seq data. Through biclustering, scBC enables the analysis of perturbations in functional gene modules at the single-cell level. Applying the scBC framework to AD snRNA-seq data reveals the perturbations within gene modules across distinct cell groups and sheds light on gene-cell correlations during AD progression. Notably, our method helps to overcome common challenges in single-cell data analysis, including batch effects and dropout events. Incorporating prior knowledge further enables the framework to yield more biologically interpretable results. Comparative analyses on simulated and real-world datasets demonstrate the precision and robustness of our approach compared to other state-of-the-art biclustering methods. scBC holds potential for unraveling the mechanisms underlying polygenic diseases characterized by intricate gene coexpression patterns.

Design and validation of a new scale for prehospital evaluation of stroke and large vessel occlusion.

Background: Rapid recognition of acute stroke and large vessel occlusion (LVO) is essential in prehospital triage for timely reperfusion treatment. Objective: This study aimed to develop and validate a new screening tool for both stroke and LVO in an urban Chinese population. Methods: This study included patients with suspected stroke who were transferred to our hospital by emergency medical services between July 2017 and June 2021. The population was randomly partitioned into training (70%) and validation (30%) groups. The Staring-Hypertension-atrIal fibrillation-sPeech-weakneSs (SHIPS) scale, consisting of both clinical and medical history information, was generated based on multivariate logistic models. The predictive ability of the SHIPS scale was evaluated and compared with other scales using receiver operating characteristic (ROC) curve comparison analysis. Results: A total of 400 patients were included in this analysis. In the training group (n = 280), the SHIPS scale showed a sensitivity of 90.4% and specificity of 60.8% in predicting stroke and a sensitivity of 75% and specificity of 61.5% in predicting LVO. In the validation group (n = 120), the SHIPS scale was not inferior to Stroke 1-2-0 (p = 0.301) in predicting stroke and was significantly better than the Cincinnati Stroke Triage Assessment Tool (C-STAT; formerly CPSSS) and the Prehospital Acute Stroke Severity scale (PASS) (all p < 0.05) in predicting LVO. In addition, including medical history in the scale was significantly better than using symptoms alone in detecting stroke (training group, 0.853 versus 0.818; validation group, 0.814 versus 0.764) and LVO (training group, 0.748 versus 0.722; validation group, 0.825 versus 0.778). Conclusion: The SHIPS scale may serve as a superior screening tool for stroke and LVO identification in prehospital triage. Including medical history in the SHIPS scale improves the predictive value compared with clinical symptoms alone.

Delayed filling of the superficial middle cerebral vein in acute large artery occlusion.

Objective: This study aimed to determine whether baseline delayed filling of the superficial middle cerebral vein (SMCV) was an independent cause of stroke prognosis in patients with acute anterior large vessel occlusion (LVO). Methods: Consecutive patients with acute LVO [middle cerebral artery M1 ± intracranial internal carotid artery (ICA)] between March 2019 and May 2020 were included. Delayed SMCV was defined as delayed filling of SMCV in the affected side compared with the normal side throughout the venous phase on four-dimensional computed tomographic angiography (4D-CTA) reconstructed from CT perfusion imaging. The modified Rankin scale (mRS) was used to evaluate the prognosis of these patients 3 months after stroke. Results: Of 54 patients in total, 47 (87.0%) patients presented with baseline delayed SMCV, and 36 (76.6%) patients achieved SMCV reversal (ipsilateral delayed SMCV reversed to bilateral symmetrical SMCV) after reperfusion therapy. Successful reperfusion was independently associated with SMCV reversal [odds ratio (OR) = 69.328, 95% confidence interval (CI) = 2.818-175.342]. A significant association between baseline SMCV delay and a 3-month poor outcome (OR = 19.623, 95% CI = 1.567-245.727, p = 0.021) was observed using a multivariable regression analysis. Compared with patients with persistent delayed SMCV, patients with reversed SMCV did not show a significant difference in the risk of a 3-month poor outcome (OR = 1.177, 95% CI = 0.147-9.448). Conclusions: In patients with acute LVO, baseline delayed SMCV was an independent cause of poor stroke prognosis, and SMCV reversal cannot reverse the 3-month stroke prognosis. Therefore, the evaluation of baseline SMCV filling status should be strengthened in clinical practice.

SGLT-2i and Risk of Malignancy in Type 2 Diabetes: A Meta-Analysis of Randomized Controlled Trials.

Background: Currently, the association between sodium-glucose cotransporter 2 inhibitor (SGLT-2i) and malignancy risk has yet to be fully elucidated. This meta-analysis aimed to determine the relationship between SGLT-2i and malignancy risk in type 2 diabetes (T2D) patients. Methods: We searched PubMed, ScienceDirect, EMBASE, Cochrane Central Register of Controlled Trials, and Web of Science to identify randomized controlled trials (RCTs) published up to August 2020 related to T2D patients treated with SGLT-2i vs. placebo or other hypoglycemic agents. The meta-analysis's primary outcome was malignancies' incidence, and the results were evaluated using risk ratio (RR) and 95% confidence interval (CI). Results: We reviewed 76 articles (77 RCTs), comprising 45,162 and 43,811 patients in SGLT-2i and control groups, respectively. Compared with the control group, SGLT-2i had no significant association with augmented overall malignancy risk in T2D patients (RR = 1.05, 95% CI = 0.97-1.14, P = 0.20), but ertugliflozin may upsurge the risk (RR = 1.80, 95% CI = 1.02-3.17, P = 0.04). Compared with active hypoglycemic agents, dapagliflozin may increase (RR = 2.71, 95% CI = 1.46-6.43, P = 0.02) and empagliflozin may decrease (RR = 0.67, 95% CI = 0.45-0.98, P = 0.04) the malignancy risk. Compared with placebo, empagliflozin may exhibit risk increase (RR = 1.25, 95% CI = 1.05-1.49, P = 0.01), primarily in digestive system (RR = 1.48, 95% CI = 0.99-2.21, P = 0.05). Conclusions: Our results proposed that in diverse comparisons, ertugliflozin and dapagliflozin seemed to increase the malignancy risk in T2D patients. Empagliflozin may cause malignancy risk reduction compared with active hypoglycemic agents but increase overall risk primarily in the digestive system compared with placebo. In short, the relationship between SGLT-2i and malignancy in T2D patients remains unclear.