The effects of tirzepatide, a dual glucose-dependent insulinotropic polypeptide and glucagon-like peptide-1 receptor agonist, as an addition to insulin glargine for treatment of type 2 diabetes have not been described. OBJECTIVE To assess the efficacy and safety of tirzepatide added to insulin glargine in patients with type 2 diabetes with inadequate glycemic control.DESIGN, SETTING, AND PARTICIPANTS Randomized phase 3 clinical trial conducted at 45 medical research centers and hospitals in 8 countries (enrollment from August 30, 2019, to March 20, 2020 follow-up completed January 13, 2021) in 475 adults with type 2 diabetes and inadequate glycemic control while treated with once-daily insulin glargine with or without metformin.INTERVENTIONS Patients were randomized in a 1:1:1:1 ratio to receive once-weekly subcutaneous injections of 5-mg (n = 116), 10-mg (n = 119), or 15-mg (n = 120) tirzepatide or volume-matched placebo (n = 120) over 40 weeks. Tirzepatide was initiated at 2.5 mg/week and escalated by 2.5 mg every 4 weeks until the assigned dose was achieved. MAIN OUTCOMES AND MEASURESThe primary end point was mean change from baseline in glycated hemoglobin A 1c (HbA 1c ) at week 40. The 5 key secondary end points included mean change in body weight and percentage of patients achieving prespecified HbA 1c levels. RESULTS Among 475 randomized participants (211 [44%] women; mean [SD] age, 60.6 [9.9] years; mean [SD] HbA 1c , 8.31% [0.85%]), 451 (94.9%) completed the trial. Treatment was prematurely discontinued by 10% of participants in the 5-mg tirzepatide group, 12% in the 10-mg tirzepatide group, 18% in the 15-mg tirzepatide group, and 3% in the placebo group. At week 40, mean HbA 1c change from baseline was −2.40% with 10-mg tirzepatide and −2.34% with 15-mg tirzepatide vs −0.86% with placebo (10 mg: difference vs placebo, −1.53% [97.5% CI, −1.80% to −1.27%]; 15 mg: difference vs placebo, −1.47% [97.5% CI, −1.75% to −1.20%]; P < .001 for both). Mean HbA 1c change from baseline was −2.11% with 5-mg tirzepatide (difference vs placebo, −1.24% [95% CI, −1.48% to −1.01%]; P < .001]). Mean body weight change from baseline was −5.4 kg with 5-mg tirzepatide, −7.5 kg with 10-mg tirzepatide, −8.8 kg with 15-mg tirzepatide and 1.6 kg with placebo (5 mg: difference, −7.1 kg [95% CI, −8.7 to −5.4]; 10 mg: difference, −9.1 kg [95% CI, −10.7 to −7.5]; 15 mg: difference, −10.5 kg [95% CI, −12.1 to −8.8]; P < .001 for all). Higher percentages of patients treated with tirzepatide vs those treated with placebo had HbA 1c less than 7% (85%-90% vs 34%; P < .001 for all). The most common treatment-emergent adverse events in the tirzepatide groups vs placebo group were diarrhea (12%-21% vs 10%) and nausea (13%-18% vs 3%).CONCLUSIONS AND RELEVANCE Among patients with type 2 diabetes and inadequate glycemic control despite treatment with insulin glargine, the addition of subcutaneous tirzepatide, compared with placebo, to titrated insulin glargine resulted in statistically significant improvements in glycemic control after 40 weeks.

Multiple cortical areas contribute to visual processing in mice. However, the functional organization and development of higher visual areas are unclear. Here, we used intrinsic signal optical imaging and 2-photon calcium imaging to map visual responses in adult and developing mice. We found that visually driven activity was well-correlated among higher visual areas within two distinct subnetworks resembling the dorsal and ventral visual streams. Visual response magnitude in dorsal stream areas slowly increased over the first two weeks of visual experience. By contrast, ventral stream areas exhibited strong responses shortly after eye opening. Neurons in a dorsal stream area showed little change in their tuning sharpness to oriented gratings while those in a ventral stream area increased stimulus selectivity and expanded their receptive fields significantly. Together, these findings provide a functional basis for grouping subnetworks of mouse visual areas and revealed stream differences in the development of receptive field properties.

Supplementary data are available at Bioinformatics online.

IMPORTANCE Breast reconstruction has the potential to improve a person’s body image and quality of life but has important risks. Variations in who undergoes breast reconstruction have led to questions about the quality of patient decisions. OBJECTIVE To assess the quality of patient decisions about breast reconstruction. DESIGN, SETTING, AND PARTICIPANTS A prospective, cross-sectional survey study was conducted from June 27, 2012, to February 28, 2014, at a single, academic, multidisciplinary oncology clinic among women planning to undergo mastectomy for stage I to III invasive ductal or lobular breast cancer, ductal carcinoma in situ, or prophylaxis. EXPOSURES Mastectomy only and mastectomy with reconstruction. MAIN OUTCOME AND MEASURES Knowledge, as ascertained using the Decision Quality Instrument; preference concordance, based on rating and ranking of key attributes; and decision quality, defined as having knowledge of 50% or more and preference concordance. RESULTS During the 20-month period, 214 patients were eligible, 182 were approached, and 32 missed. We enrolled 145 patients (79.7% enrollment rate), and received surveys from 131 patients (72.0% participation rate). Five participants became ineligible. The final study population was 126 patients. Among the 126 women in the study (mean [SD] age, 53.2 [12.1] years), the mean (SD) knowledge score was 58.5% (16.2%) and did not differ by treatment group (mastectomy only, 55.2% [15.0%]; mastectomy with reconstruction, 60.5% [16.5%]). A total of 82 of 123 participants (66.7%) had a calculated treatment preference of mastectomy only; 39 of these women (47.6%) underwent mastectomy only. A total of 41 participants (32.5%) had a calculated treatment preference of mastectomy with reconstruction; 36 of these women (87.8%) underwent mastectomy with reconstruction. Overall, 52 of 120 participants (43.3%) made a high-quality decision. In multivariable analysis, white race/ethnicity (odds ratio [OR], 2.72; 95% CI, 1.00–7.38; P = .05), having private insurance (OR, 1.61; 95% CI, 1.35–1.93; P < .001), having a high school education or less (vs some college) (OR, 4.84; 95% CI, 1.22–19.21; P = .02), having a college degree (vs some college) (OR, 1.95; 95% CI, 1.53–2.49; P < .001), and not having a malignant neoplasm (eg, BRCA carriers) (OR, 3.13; 95% CI, 1.25–7.85; P = .01) were independently associated with making a high-quality decision. CONCLUSIONS AND RELEVANCE A minority of patients undergoing mastectomy in a single academic center made a high-quality decision about reconstruction. Shared decision making is needed to support decisions about breast reconstruction.

Clustering is an essential step in the analysis of single cell RNA-seq (scRNA-seq) data to shed light on tissue complexity including the number of cell types and transcriptomic signatures of each cell type. Due to its importance, novel methods have been developed recently for this purpose. However, different approaches generate varying estimates regarding the number of clusters and the single-cell level cluster assignments. This type of unsupervised clustering is challenging and it is often times hard to gauge which method to use because none of the existing methods outperform others across all scenarios. We present SAME-clustering, a mixture model-based approach that takes clustering solutions from multiple methods and selects a maximally diverse subset to produce an improved ensemble solution. We tested SAME-clustering across 15 scRNA-seq datasets generated by different platforms, with number of clusters varying from 3 to 15, and number of single cells from 49 to 32 695. Results show that our SAME-clustering ensemble method yields enhanced clustering, in terms of both cluster assignments and number of clusters. The mixture model ensemble clustering is not limited to clustering scRNA-seq data and may be useful to a wide range of clustering applications.