Personalized chemotherapy selection for patients with triple-negative breast cancer using deep learning.

Background: Potential uncertainties and overtreatment exist in adjuvant chemotherapy for triple-negative breast cancer (TNBC) patients. Objectives: This study aims to explore the performance of deep learning (DL) models in personalized chemotherapy selection and quantify the impact of baseline characteristics on treatment efficacy. Methods: Patients who received treatment recommended by models were compared to those who did not. Overall survival for treatment according to model recommendations was the primary outcome. To mitigate bias, inverse probability treatment weighting (IPTW) was employed. A mixed-effect multivariate linear regression was employed to visualize the influence of certain baseline features of patients on chemotherapy selection. Results: A total of 10,070 female TNBC patients met the inclusion criteria. Treatment according to Self-Normalizing Balanced (SNB) individual treatment effect for survival data model recommendations was associated with a survival benefit (IPTW-adjusted hazard ratio: 0.53, 95% CI, 0.32-8.60; IPTW-adjusted risk difference: 12.90, 95% CI, 6.99-19.01; IPTW-adjusted the difference in restricted mean survival time: 5.54, 95% CI, 1.36-8.61), which surpassed other models and the National Comprehensive Cancer Network guidelines. No survival benefit for chemotherapy was seen for patients not recommended to receive this treatment. SNB predicted older patients with larger tumors and more positive lymph nodes are the optimal candidates for chemotherapy. Conclusion: These findings suggest that the SNB model may identify patients with TNBC who could benefit from chemotherapy. This novel analytical approach may provide debiased individual survival information and treatment recommendations. Further research is required to validate these models in clinical settings with more features and outcome measurements.

Chimeric antigen receptor-modified T cells therapy in prostate cancer: A comprehensive review on the current state and prospects.

Recent immunotherapy research has focused on chimeric antigen receptor-modified T cells (CAR-Ts). CAR-T therapies have been clinically applied to manage hematologic malignancies with satisfactory effectiveness. However, the application of CAR-T immunotherapy in solid tumors remains challenging. Even so, current CAR-T immunotherapies for prostate cancer (PCa) have shown some promise, giving hope to patients with advanced metastatic PCa. This review aimed to elucidate different types of prostate tumor-associated antigen targets, such as prostate-specific membrane antigen and prostate stem cell antigen, and their effects. The current status of the corresponding targets in clinical research through their applications was also discussed. To improve the efficacy of CAR-T immunotherapy, we addressed the possible applications of multimodal immunotherapy, chemotherapy, and CAR-T combined therapies. The obstacles of solid tumors were concisely elaborated. Further studies should aim to discover novel potential targets and establish new models by overcoming the inherent barriers of solid tumors, such as tumor heterogeneity and the immunosuppressive nature of the tumor microenvironment.

What measures are needed to achieve a tobacco endgame target? A Singapore-based simulation study.

BACKGROUND: An increasing number of countries are pursuing a tobacco 'endgame'. We sought to determine the combination of measures it would take to achieve a tobacco endgame in the city-state of Singapore. METHODS: Using an open-cohort microsimulation model, we estimated the impact of existing measures (quit programmes, tobacco taxes, flavours ban) and more novel measures (very low nicotine cap, tobacco-free generation, raising the minimum legal age to 25 years), and combinations thereof, on smoking prevalence in Singapore over a 50-year horizon. We used Markov Chain Monte Carlo to estimate transition probabilities between the states of never smoker, current smoker and former smoker, updating each individual's state across each year with prior distributions derived from national survey data. RESULTS: Without new measures, smoking prevalence is expected to rebound from 12.2% (2020) to 14.8% (2070). The only scenarios to achieve a tobacco endgame target within a decade are those combining a very low nicotine cap with a flavours ban. A nicotine cap or tobacco-free generation alone also achieve endgame targets, but after 20 and 39 years, respectively. Taxes, quit programmes, a flavours ban and minimum legal age increase do augment the impact of other measures, but even when combined are insufficient to achieve a tobacco endgame target within 50 years. CONCLUSION: In Singapore, achieving a tobacco endgame within a decade requires a very low nicotine cap coupled with a tobacco flavours ban, although this target can also be achieved in the long term (within 50 years) with a tobacco-free generation.

Evaluating the public health impact of partial and full tobacco flavour bans: A simulation study.

BACKGROUND: Tobacco flavours such as menthol and fruits, which appeal to youth, remain unregulated in Western Pacific countries. Our goal was to evaluate the potential impact of tobacco flavour bans in Singapore, which has the region's highest flavoured cigarette market share. METHODS: Using an open-cohort microsimulation model, we estimated the impact of full ban and partial ban (excluding menthol and clove) scenarios versus the status quo (no ban) over a 50-year horizon. We used a Markov chain with four states (never, unflavoured, flavoured and ex-smokers), updating each individual's state across each year. We estimated between-state transition probabilities using Markov chain Monte Carlo, with prior distributions derived from national survey data. FINDINGS: Without a ban, smoking prevalence gradually increases from 12.7% (2018) to 15.2% (2068). In both ban scenarios, smoking prevalence decreases immediately after the ban: by 1.6% points in the full ban, and 0.4% points in the partial ban scenario. In addition, there is a sustained long-term impact as fewer initiate. In the full ban scenario, smoking prevalence decreases to 10.6% by 2068 with a cumulative gain of over 40,000 QALYs. In the partial ban scenario, it remains stable at 12.5% with a cumulative gain of over 20,000 QALYs. INTERPRETATIONS: A tobacco flavours ban would reap substantial public health benefits in countries that, like Singapore, have a large flavoured cigarette market share, especially with a full ban compared to a partial ban not covering menthol or clove-flavoured cigarettes. FUNDING: This study was funded by the Singapore Ministry of Health.

Determining quarantine length and testing frequency for international border opening during the COVID-19 pandemic.

BACKGROUND: The COVID-19 pandemic has resulted in the closure or partial closure of international borders in almost all countries. Here, we investigate the efficacy of imported case detection considering quarantine length and different testing measures for travellers on arrival. METHODS: We examine eight broad border control strategies from utilizing quarantine alone, pre-testing, entry and exit testing, and testing during quarantine. In comparing the efficacy of these strategies, we calculate the probability of detecting travellers who have been infected up to 2 weeks pre-departure according to their estimated incubation and infectious period. We estimate the number of undetected infected travellers permitted entry for these strategies across a prevalence range of 0.1-2% per million travellers. RESULTS: At 14-day quarantine, on average 2.2% (range: 0.5-8.2%) of imported infections are missed across the strategies, leading to 22 (5-82) imported cases at 0.1% prevalence per million travellers, increasing up to 430 (106-1641) at 2%. The strategy utilizing exit testing results in 3.9% (3.1-4.9%) of imported cases being missed at 7-day quarantine, down to 0.4% (0.3-0.7%) at 21-day quarantine, and the introduction of daily testing, as the most risk averse strategy, reduces the proportion further to 2.5-4.2% at day 7 and 0.1-0.2% at day 21 dependent on the tests used. Rapid antigen testing every 3 days in quarantine leads to 3% being missed at 7 days and 0.7% at 14 days, which is comparable to PCR testing with a 24-hour turnaround. CONCLUSIONS: Mandatory testing, at a minimal of pre-testing and on arrival, is strongly recommended where the length of quarantining should then be determined by the destination country's level of risk averseness, pandemic preparedness and origin of travellers. Repeated testing during quarantining should also be utilized to mitigate case importation risk and reduce the quarantining duration required.

Laser-CMT Hybrid Welding-Brazing of Al/Steel Butt Joint: Weld Formation, Intermetallic Compounds, and Mechanical Properties.

6A01-T5 aluminum alloy and SUS301L-DLT austenitic stainless steel sheets were welded by a laser-cold metal transfer (CMT) hybrid welding-brazing method with ER5183 filler wire. We researched the weld forming, intermetallic compounds, and mechanical character, which are influenced by laser power, wire feeding speed, and welding speed. Well-formed joints with uniformly distributed interface layers were obtained under certain parameters. The spreading and wetting distance on the steel upper surface increased initially and then decreased as the laser power increased, and increased progressively as the wire feeding speed increased or welding speed decreased. There were both Fe2Al5 and Fe4Al13 in the interfacial intermetallic compounds (IMCs) layer. The thickness was controlled to within 2.0-6.9 µm. The thickness of the IMCs layer increased as the heat input increased; however, the increasing rate decreased gradually. The tensile strength of the joints was not only completely dependent on the thickness of the IMCs, but also on the spreading and wetting distance on the steel surface. The highest tensile strength could reach up to 188.7 MPa, which is about 77.1% of that of the base aluminum alloy. The tensile sample fracture occurred at the IMCs layer, and regional metallurgical bonding happened in the interface layer.