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Background: Artificial intelligence approaches can integrate complex features and can be used to predict a patient’s risk of developing lung cancer, thereby decreasing the need for unnecessary and expensive diagnostic interventions. Objective: The aim of this study was to use electronic medical records to prescreen patients who are at risk of developing lung cancer. Methods: We randomly selected 2 million participants from the Taiwan National Health Insurance Research Database who received care between 1999 and 2013. We built a predictive lung cancer screening model with neural networks that were trained and validated using pre-2012 data, and we tested the model prospectively on post-2012 data. An age- and gender-matched subgroup that was 10 times larger than the original lung cancer group was used to assess the predictive power of the electronic medical record. Discrimination (area under the receiver operating characteristic curve [AUC]) and calibration analyses were performed. Results: The analysis included 11,617 patients with lung cancer and 1,423,154 control patients. The model achieved AUCs of 0.90 for the overall population and 0.87 in patients ≥55 years of age. The AUC in the matched subgroup was 0.82. The positive predictive value was highest (14.3%) among people aged ≥55 years with a pre-existing history of lung disease. Conclusions: Our model achieved excellent performance in predicting lung cancer within 1 year and has potential to be deployed for digital patient screening. Convolution neural networks facilitate the effective use of EMRs to identify individuals at high risk for developing lung cancer.

Statins have been shown to be a beneficial treatment as chemotherapy and target therapy for lung cancer. This study aimed to investigate the effectiveness of statins in combination with epidermal growth factor receptor‐tyrosine kinase inhibitor therapy for the resistance and mortality of lung cancer patients. A population‐based cohort study was conducted using the Taiwan Cancer Registry database. From January 1, 2007, to December 31, 2012, in total 792 non‐statins and 41 statins users who had undergone EGFR‐TKIs treatment were included in this study. All patients were monitored until the event of death or when changed to another therapy. Kaplan‐Meier estimators and Cox proportional hazards regression models were used to calculate overall survival. We found that the mortality was significantly lower in patients in the statins group compared with patients in the non‐statins group (4‐y cumulative mortality, 77.3%; 95% confidence interval (CI), 36.6%‐81.4% vs. 85.5%; 95% CI, 78.5%‐98%; P = .004). Statin use was associated with a reduced risk of death in patients the group who had tumor sizes <3 cm (hazard ratio [HR], 0.51, 95% CI, 0.29‐0.89) and for patients in the group who had CCI scores <3 (HR, 0.6; 95% CI, 0.41‐0.88; P = .009). In our study, statins were found to be associated with prolonged survival time in patients with lung cancer who were treated with EGFR‐TKIs and played a synergistic anticancer role. In this article, we describe the use of statins on the beneficial mortality of lung cancer patients with EGFR‐TKIs therapy. We found that statins were associated with prolonged survival time in patients with lung cancer who were taking EGFR‐TKIs. These could be playing a synergic anticancer role during the TKI treatment period, as well as improving quality of life worldwide and medical practice overall.

This study aimed to perform a preliminary screen of various waters for pollution by emerging contaminants and identifying potential cross-contamination problems in aquaculture systems. Specifically, the occurrence and distribution of 110 emerging contaminants (49 antibiotics, 49 other pharmaceuticals, and 12 industrial/household compounds) in 14 aquaculture sites (fish, shrimp, and shellfish ponds) and three surrounding aquatic environments in Taiwan were investigated. All the detected compounds were at nanogram per liter to sub-microgram per liter levels. Six pharmaceuticals that occurred at high concentrations and frequencies were ibuprofen (788 ng/L), lincomycin (624 ng/L), flumequine (331 ng/L), caffeine (276 ng/L), ifosfamide (220 ng/L), and cephalexin (172 ng/L). Other commonly detected emerging contaminants (with detection frequencies > 70%) were sulfamethoxazole, erythromycin-H2O, atenolol, methadone, benzotriazole, tolyltriazole, perfluorobutane sulfonate (PFBS), perfluoroheptanoic acid (PFHpA), perfluorooctanoate (PFOA), and perfluorononanoic acid (PFNA). This work demonstrated the impact of aquaculture activities (i.e., usage of antibiotics) on the surrounding aquatic environments and, at the same time, how the surrounding anthropogenic activities impact aquaculture waters. Cross-contamination was observed between these two aquatic systems; emerging contaminants resulting from human activities, such as perfluorinated chemicals, anticorrosive substances, and anticancer and abused drugs, from the surrounding waters were found to be introduced into the aquaculture systems.

This review presents a critical assessment of emerging microfluidic technologies for the application on biological productions of biofuels and other chemicals from microalgae. Comparisons of cell culture designs for the screening of microalgae strains and growth conditions are provided with three categories: mechanical traps, droplets, or microchambers. Emerging technologies for the in situ characterization of microalgae features and metabolites are also presented and evaluated. Biomass and secondary metabolite productivities obtained at microscale are compared with the values obtained at bulk scale to assess the feasibility of optimizing large-scale operations using microfluidic platforms. The recent studies in microsystems for microalgae pretreatment, fractionation and extraction of metabolites are also reviewed. Finally, comments toward future developments (high-pressure/-temperature process; solvent-resistant devices; omics analysis, including genome/epigenome, proteome, and metabolome; biofilm reactors) of microfluidic techniques for microalgae applications are provided.

Background Single-cell droplet microfluidics is an important platform for high-throughput analyses and screening because it provides an independent and compartmentalized microenvironment for reaction or cultivation by coencapsulating individual cells with various molecules in monodisperse microdroplets. In combination with microbial biosensors, this technology becomes a potent tool for the screening of mutant strains. In this study, we demonstrated that a genetically engineered yeast strain that can fluorescently sense agonist ligands via the heterologous expression of a human G-protein-coupled receptor (GPCR) and concurrently secrete candidate peptides is highly compatible with single-cell droplet microfluidic technology for the high-throughput screening of new agonistically active peptides. Results The water-in-oil microdroplets were generated using a flow-focusing microfluidic chip to encapsulate engineered yeast cells coexpressing a human GPCR [i.e., angiotensin II receptor type 1 (AGTR1)] and a secretory agonistic peptide [i.e., angiotensin II (Ang II)]. The single yeast cells cultured in the droplets were then observed under a microscope and analyzed using image processing incorporating machine learning techniques. The AGTR1-mediated signal transduction elicited by the self-secreted Ang II peptide was successfully detected via the expression of a fluorescent reporter in single-cell yeast droplet cultures. The system could also distinguish Ang II analog peptides with different agonistic activities. Notably, we further demonstrated that the microenvironment of the single-cell droplet culture enabled the detection of rarely existing positive (Ang II-secreting) yeast cells in the model mixed cell library, whereas the conventional batch-culture environment using a shake flask failed to do so. Thus, our approach provided compartmentalized microculture environments, which can prevent the diffusion, dilution, and cross-contamination of peptides secreted from individual single yeast cells for the easy identification of GPCR agonists. Conclusions We established a droplet-based microfluidic platform that integrated an engineered yeast biosensor strain that concurrently expressed GPCR and self-secreted the agonistic peptides. This offers individually isolated microenvironments that allow the culture of single yeast cells secreting these peptides and gaging their signaling activities, for the high-throughput screening of agonistic peptides. Our platform base on yeast GPCR biosensors and droplet microfluidics will be widely applicable to metabolic engineering, environmental engineering, and drug discovery.

Background A bronchopleural fistula (BPF) occurs when an abnormal connection forms between the bronchial tubes and pleural cavity, often due to surgery, infection, trauma, radiation, or chemotherapy. The outcomes of both surgical and bronchoscopic treatments frequently prove to be unsatisfactory. Case presentation Here, we report a case of successful bronchoscopic free fat pad transplantation combined with platelet-rich plasma, effectively addressing a post-lobectomy BPF. Contrast-enhanced chest tomography revealed pleural thickening with heterogeneous consolidations over the right upper and middle lobes, indicative of destructive lung damage and bronchiectasis. The patient underwent thoracoscopic bilobectomy of the lungs. During surgery, severe adhesions and calcification of the chest wall and lung parenchyma were observed. The entire hilar structure was calcified, presenting challenges for dissection, despite the assistance of energy devices. Bronchoscopic intervention was required, during which two abdominal subcutaneous fat pads were retrieved. Conclusion This innovative approach offers promise in the management of BPF and signals potential advancements in enhancing treatment efficacy and patient recovery.

Background: Chinese herbal medicine (CHM), a commonly used alternative therapy, has been reported to reduce the side effects of cancer treatments and improve the quality of life (QOL) in breast cancer (BC) patients. However, there is limited research on the effects of CHM in BC patients experiencing hot flushes (HFs) during adjuvant chemotherapy. We conducted a non-randomized controlled trial to evaluate the effectiveness of CHM on side effects, QOL, and changes in meridian electrodermal activity. Methods: Forty-eight patients with stage I-III BC undergoing adjuvant chemotherapy were non-randomly assigned to either a 24-week CHM treatment group or a 24-week non-CHM control group. The CHM intervention involved a combination of Jia Wei Xiao Yao San and Er Zhi Wan in a 3:1 ratio, with a total daily dose of 4 g taken 3 times a day. The primary outcome was the occurrence of 10 or more HFs per week and the severity of symptoms, rated using a visual analog scale (1-10). Secondary outcomes included the Functional Assessment of Cancer Therapy-Breast Cancer questionnaire to assess health-related QOL, and meridian energy analysis to measure skin electrical conductance and sympathetic activity. The difference between the CHM and non-CHM groups in individual changes from baseline to week 24 was evaluated using an independent t-test. Results: A total of 43 participants completed the study, with 25 in the CHM group and 18 in the control group. The CHM group showed a statistically significant reduction in HF frequency at 12 and 24 weeks and a decrease in HF severity at 12 weeks compared to the control group (P < .05). Physical well-being and specific concerns scores also improved significantly over time in the CHM group compared to the control group (P < .05). While CHM treatment did not lead to significant changes in overall electrical conductance at acupoints (P = .251), it did significantly affect specific meridians, including the heart, liver, and kidney (P = .032, P = .035, and P = .035, respectively). Additionally, sympathetic activity was reduced in the CHM group after completing chemotherapy (P = .045). Conclusions: CHM therapy appears to have a preventive effect on chemotherapy-related HFs in BC patients and is safe, with no severe adverse effects observed.

This study aims to investigate the efficacy of lipid induction in Scenedesmus abundans by adding the effluent from dark fermentation of biohydrogen production. Four sets of experiments were conducted: control (sufficient nitrogen), nitrogen depletion, low concentration (0.3×) effluent addition, and high concentration (0.5×) effluent addition. The addition of low concentration effluent produced the highest biomass and lipid yields of 2.831 g/L and 1.238 g/L, corresponding to a lipid abundance of 43.72 wt%. Furthermore, S. abundans had high removal efficiencies for volatile fatty acids in the effluent (formic acid 100%, acetic acid 100%, propionic acid 98%, lactic acid 84%, and butyric acid 68%), and this is the first study demonstrating the ability of S. abundans in using formic acid and lactic acid to produce biomass and lipids. These results show that S. abundans have great abilities in simultaneous reducing organic acids in the effluent and producing valuable metabolites.

Background Vitamin D supplementation may prevent acute respiratory infections (ARIs). This study aimed to identify the optimal methods of vitamin D supplementation. Methods PubMed, Embase, Cochrane Central Register of Controlled Trials, Web of Science, and the ClinicalTrials.gov registry were searched from database inception through July 13, 2023. Randomized-controlled trials (RCTs) were included. Data were pooled using random-effects model. The primary outcome was the proportion of participants with one or more ARIs. Results The analysis included 43 RCTs with 49320 participants. Forty RCTs were considered to be at low risk for bias. The main pairwise meta-analysis indicated there were no significant preventive effects of vitamin D supplementation against ARIs (risk ratio [RR]: 0.99, 95% confidence interval [CI]: 0.97 to 1.01, I 2  = 49.6%). The subgroup dose–response meta-analysis indicated that the optimal vitamin D supplementation doses ranged between 400–1200 IU/day for both summer-sparing and winter-dominant subgroups. The subgroup pairwise meta-analysis also revealed significant preventive effects of vitamin D supplementation in subgroups of daily dosing (RR: 0.92, 95% CI: 0.85 to 0.99, I 2  = 55.7%, number needed to treat [NNT]: 36), trials duration < 4 months (RR: 0.81, 95% CI: 0.67 to 0.97, I 2  = 48.8%, NNT: 16), summer-sparing seasons (RR: 0.85, 95% CI: 0.74 to 0.98, I 2  = 55.8%, NNT: 26), and winter-dominant seasons (RR: 0.79, 95% CI: 0.71 to 0.89, I 2  = 9.7%, NNT: 10). Conclusion Vitamin D supplementation may slightly prevent ARIs when taken daily at doses between 400 and 1200 IU/d during spring, autumn, or winter, which should be further examined in future clinical trials.

Background/Objectives: Clear aligner therapy has become a mainstream alternative to fixed orthodontics due to its versatility. However, the variability in thermoforming and the limited validation of digital workflows remain major barriers to reproducibility and predictability. Methods: This study addresses that gap by presenting a proof-of-concept digital workflow for clear aligner manufacturing by integrating additive manufacturing (AM), thermoforming simulation, and finite element analysis (FEA). Dental models were 3D-printed and thermoformed under clinically relevant pressures (400 kPa positive and −90 kPa negative). Results and Discussion: Geometric accuracy was quantified using CloudCompare v2.13.0, showing that positive-pressure thermoforming reduced maximum deviations from 1.06 mm to 0.4 mm, with all deviations exceeding the expanded measurement uncertainty. Thickness simulations of PETG sheets (0.5 and 0.75 mm) showed good agreement with experimental values across seven validation points, with errors <10% and overlapping 95% confidence intervals. Stress analysis indicated that force transmission was localized at the aligner–attachment interface, consistent with expected orthodontic mechanics. Conclusions: By quantifying accuracy and mechanical behavior through numerical and experimental validation, this framework demonstrates how controlled thermoforming and simulation-guided design can enhance aligner consistency, reduce adjustments, and improve treatment predictability.