Aside from centrally induced trained immunity in the bone marrow (BM) and peripheral blood by parenteral vaccination or infection, evidence indicates that mucosal-resident innate immune memory can develop via a local inflammatory pathway following mucosal exposure. However, whether mucosal-resident innate memory results from integrating distally generated immunological signals following parenteral vaccination/infection is unclear. Here we show that subcutaneous Bacillus Calmette–Guérin (BCG) vaccination can induce memory alveolar macrophages (AMs) and trained immunity in the lung. Although parenteral BCG vaccination trains BM progenitors and circulating monocytes, induction of memory AMs is independent of circulating monocytes. Rather, parenteral BCG vaccination, via mycobacterial dissemination, causes a time-dependent alteration in the intestinal microbiome, barrier function and microbial metabolites, and subsequent changes in circulating and lung metabolites, leading to the induction of memory macrophages and trained immunity in the lung. These data identify an intestinal microbiota-mediated pathway for innate immune memory development at distal mucosal tissues and have implications for the development of next-generation vaccine strategies against respiratory pathogens.

In recent times, technologies such as machine learning and deep learning have played a vital role in providing assistive solutions to a medical domain’s challenges. They also improve predictive accuracy for early and timely disease detection using medical imaging and audio analysis. Due to the scarcity of trained human resources, medical practitioners are welcoming such technology assistance as it provides a helping hand to them in coping with more patients. Apart from critical health diseases such as cancer and diabetes, the impact of respiratory diseases is also gradually on the rise and is becoming life-threatening for society. The early diagnosis and immediate treatment are crucial in respiratory diseases, and hence the audio of the respiratory sounds is proving very beneficial along with chest X-rays. The presented research work aims to apply Convolutional Neural Network based deep learning methodologies to assist medical experts by providing a detailed and rigorous analysis of the medical respiratory audio data for Chronic Obstructive Pulmonary detection. In the conducted experiments, we have used a Librosa machine learning library features such as MFCC, Mel-Spectrogram, Chroma, Chroma (Constant-Q) and Chroma CENS. The presented system could also interpret the severity of the disease identified, such as mild, moderate, or acute. The investigation results validate the success of the proposed deep learning approach. The system classification accuracy has been enhanced to an ICBHI score of 93%. Furthermore, in the conducted experiments, we have applied K-fold Cross-Validation with ten splits to optimize the performance of the presented deep learning approach.

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Recently, photodynamic therapy (PDT) has found wide application as a noninvasive treatment modality for several cancers. However, the suboptimal delivery of photosensitizers (PSs) to the tumor site is a drawback, which inhibits the effectiveness of PDT. Hydrophobicity, strong oxygen and light dependence, and limited tissue penetrability of photosensitizers represent the major barriers to the clinical application of PDT. In order to improve biopharmaceutical properties of a clinically approved photosensitizer chlorin e6 (Ce6), we developed a nanoformulation encapsulating Ce6 in methoxy-poly(ethylene glycol)-poly(d,l-lactide) (mPEG-PLA) copolymeric micelles. The physicochemical properties, including particle size, zeta potential, encapsulation efficiency, drug loading, generation of reactive oxygen species following near-infrared light illumination (633 nm), and in vitro drug release, were determined. The therapeutic efficacy of Ce6-mPEG-PLA micelles following illumination were evaluated in vitro in both two- and three-dimensional cell culture systems by using human uterine cervix carcinoma (HeLa) and human alveolar adenocarcinoma (A549) cells in monolayers and in A549 spheroids, respectively. The mPEG-PLA micelles were stable with a particle size of 189.6 ± 14.32 nm and loaded Ce6 efficiently (encapsulation efficiency ∼75%). The Ce6-loaded micelles generated singlet oxygen at a higher concentration compared to free Ce6 in aqueous media. Ce6-mPEG-PLA micelle mediated PDT showed improved cellular internalization in both of the cell lines, resulting in enhanced cytotoxicity compared to free Ce6. In contrast, the Ce6-loaded micelles did not show any cytotoxicity in the absence of irradiation. The Ce6-loaded micelles exhibited deep penetration in the spheroids leading to phototoxicity and cellular apoptosis in the A549 spheroidal model. Results from this study indicated that the newly developed nanoformulation of Ce6 could be utilized in PDT as an effective treatment modality for solid tumors.

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