Localized fine-tuning and clinical evaluation of deep-learning based auto-segmentation (DLAS) model for clinical target volume (CTV) and organs-at-risk (OAR) in rectal cancer radiotherapy.

BACKGROUND AND PURPOSE: Various deep learning auto-segmentation (DLAS) models have been proposed, some of which have been commercialized. However, the issue of performance degradation is notable when pretrained models are deployed in the clinic. This study aims to enhance precision of a popular commercial DLAS product in rectal cancer radiotherapy by localized fine-tuning, addressing challenges in practicality and generalizability in real-world clinical settings. MATERIALS AND METHODS: A total of 120 Stage II/III mid-low rectal cancer patients were retrospectively enrolled and divided into three datasets: training (n = 60), external validation (ExVal, n = 30), and generalizability evaluation (GenEva, n = 30) datasets respectively. The patients in the training and ExVal dataset were acquired on the same CT simulator, while those in GenEva were on a different CT simulator. The commercial DLAS software was first localized fine-tuned (LFT) for clinical target volume (CTV) and organs-at-risk (OAR) using the training data, and then validated on ExVal and GenEva respectively. Performance evaluation involved comparing the LFT model with the vendor-provided pretrained model (VPM) against ground truth contours, using metrics like Dice similarity coefficient (DSC), 95th Hausdorff distance (95HD), sensitivity and specificity. RESULTS: LFT significantly improved CTV delineation accuracy (p < 0.05) with LFT outperforming VPM in target volume, DSC, 95HD and specificity. Both models exhibited adequate accuracy for bladder and femoral heads, and LFT demonstrated significant enhancement in segmenting the more complex small intestine. We did not identify performance degradation when LFT and VPM models were applied in the GenEva dataset. CONCLUSIONS: The necessity and potential benefits of LFT DLAS towards institution-specific model adaption is underscored. The commercial DLAS software exhibits superior accuracy once localized fine-tuned, and is highly robust to imaging equipment changes.

LSTrAP-denovo: Automated Generation of Transcriptome Atlases for Eukaryotic Species Without Genomes.

Despite the abundance of species with transcriptomic data, a significant number of species still lack sequenced genomes, making it difficult to study gene function and expression in these organisms. While de novo transcriptome assembly can be used to assemble protein-coding transcripts from RNA-sequencing (RNA-seq) data, the datasets used often only feature samples of arbitrarily selected or similar experimental conditions, which might fail to capture condition-specific transcripts. We developed the Large-Scale Transcriptome Assembly Pipeline for de novo assembled transcripts (LSTrAP-denovo) to automatically generate transcriptome atlases of eukaryotic species. Specifically, given an NCBI TaxID, LSTrAP-denovo can (1) filter undesirable RNA-seq accessions based on read data, (2) select RNA-seq accessions via unsupervised machine learning to construct a sample-balanced dataset for download, (3) assemble transcripts via over-assembly, (4) functionally annotate coding sequences (CDS) from assembled transcripts and (5) generate transcriptome atlases in the form of expression matrices for downstream transcriptomic analyses. LSTrAP-denovo is easy to implement, written in Python, and is freely available at https://github.com/pengkenlim/LSTrAP-denovo/.

Acute hematologic toxicity prediction using dosimetric and radiomics features in patients with cervical cancer: does the treatment regimen matter?

Background: Acute hematologic toxicity (HT) is a prevalent adverse tissue reaction observed in cervical cancer patients undergoing chemoradiotherapy (CRT), which may lead to various negative effects such as compromised therapeutic efficacy and prolonged treatment duration. Accurate prediction of HT occurrence prior to CRT remains challenging. Methods: A discovery dataset comprising 478 continuous cervical cancer patients (140 HT patients) and a validation dataset consisting of 205 patients (52 HT patients) were retrospectively enrolled. Both datasets were categorized into the CRT group and radiotherapy (RT)-alone group based on the treatment regimen, i.e., whether chemotherapy was administered within the focused RT duration. Radiomics features were derived by contouring three regions of interest (ROIs)-bone marrow (BM), femoral head (FH), and clinical target volume (CTV)-on the treatment planning CT images before RT. A comprehensive model combining the radiomics features as well as the demographic, clinical, and dosimetric features was constructed to classify patients exhibiting acute HT symptoms in the CRT group, RT group, and combination group. Furthermore, the time-to-event analysis of the discriminative ROI was performed on all patients with acute HT to understand the HT temporal progression. Results: Among three ROIs, BM exhibited the best performance in classifying acute HT, which was verified across all patient groups in both discovery and validation datasets. Among different patient groups in the discovery dataset, acute HT was more precisely predicted in the CRT group [area under the curve (AUC) = 0.779, 95% CI: 0.657-0.874] than that in the RT-alone (AUC = 0.686, 95% CI: 0.529-0.817) or combination group (AUC = 0.748, 95% CI: 0.655-0.827). The predictive results in the validation dataset similarly coincided with those in the discovery dataset: CRT group (AUC = 0.802, 95% CI: 0.669-0.914), RT-alone group (AUC = 0.737, 95% CI: 0.612-0.862), and combination group (AUC = 0.793, 95% CI: 0.713-0.874). In addition, distinct feature sets were adopted for different patient groups. Moreover, the predicted HT risk of BM was also indicative of the HT temporal progression. Conclusions: HT prediction in cervical patients is dependent on both the treatment regimen and ROI selection, and BM is closely related to the occurrence and progression of HT, especially for CRT patients.

Identifying MAGE-A4-positive tumors for TCR T cell therapies in HLA-A∗02-eligible patients.

T cell receptor (TCR) T cell therapies target tumor antigens in a human leukocyte antigen (HLA)-restricted manner. Biomarker-defined therapies require validation of assays suitable for determination of patient eligibility. For clinical trials evaluating TCR T cell therapies targeting melanoma-associated antigen A4 (MAGE-A4), screening in studies NCT02636855 and NCT04044768 assesses patient eligibility based on: (1) high-resolution HLA typing and (2) tumor MAGE-A4 testing via an immunohistochemical assay in HLA-eligible patients. The HLA/MAGE-A4 assays validation, biomarker data, and their relationship to covariates (demographics, cancer type, histopathology, tissue location) are reported here. HLA-A∗02 eligibility was 44.8% (2,959/6,606) in patients from 43 sites across North America and Europe. While HLA-A∗02:01 was the most frequent HLA-A∗02 allele, others (A∗02:02, A∗02:03, A∗02:06) considerably increased HLA eligibility in Hispanic, Black, and Asian populations. Overall, MAGE-A4 prevalence based on clinical trial enrollment was 26% (447/1,750) across 10 solid tumor types, and was highest in synovial sarcoma (70%) and lowest in gastric cancer (9%). The covariates were generally not associated with MAGE-A4 expression, except for patient age in ovarian cancer and histology in non-small cell lung cancer. This report shows the eligibility rate from biomarker screening for TCR T cell therapies and provides epidemiological data for future clinical development of MAGE-A4-targeted therapies.

Heterotopic pregnancy: a case report of intrauterine hydatidiform mole with tubal pregnancy.

We herein report a rare case of simultaneous intrauterine molar pregnancy and tubal pregnancy. A woman of childbearing age who had never been pregnant underwent an ultrasound examination 70 days after the onset of menopause. She had a history of ovulation induction. The ultrasound findings suggested a partial hydatidiform mole. She was then pathologically confirmed to have a complete hydatidiform mole after uterine suction dilation and curettage. On postoperative day 4, an ultrasound examination before discharge showed an inhomogeneous mass in the left adnexal region with mild lower abdominal pain. On postoperative day 17, the blood human chorionic gonadotropin level did not drop as expected, and a follow-up examination still indicated a mass in the left adnexal region. We were unable to rule out an ectopic hydatidiform mole. Hysteroscopy with laparoscopic exploration of the left adnexal mass and salpingotomy suggested a diagnosis of intrauterine hydatidiform mole combined with left tubal pregnancy.

Single-exposure multi-wavelength optical diffraction tomography based on space-angle dual multiplexing holography.

We present a space-angle dual multiplexing holographic recording system for realizing single-exposure multi-wavelength optical diffraction tomographic (ODT) imaging. This system is achieved by combining the principle of single-exposure multi-wavelength holographic imaging technique based on angle-division multiplexing with the principle of single-exposure ODT imaging technique based on microlens array multi-angle illuminations and space-division multiplexing. Compared with the existing multi-wavelength ODT imaging methods, it enables the holographic recording of all the diffraction tomography information of a measured specimen at multiple illumination wavelengths in a single camera exposure without any scan mechanism. Using our proposed data processing method, the multi-wavelength three-dimensional (3D) refractive index tomograms of a specimen can be eventually reconstructed from single recorded multiplexing hologram. Experimental results of a static polystyrene bead and a living C. elegans worm demonstrate the feasibility of this system.

A shifting terrain: Understanding the perspectives of walk-in physicians on their roles amid worsening primary care access in Ontario, Canada.

BACKGROUND: High-quality primary care is associated with better health outcomes and more efficient and equitable health system performance. However, the rate of primary care attachment is falling, and timely access to primary care is worsening, driving many patients to use walk-in clinics for their comprehensive primary care needs. This study sought to explore the experiences and perceived roles and responsibilities of walk-in physicians in this current climate. Methods: Qualitative interviews were conducted with nineteen physicians currently providing walk-in care in Ontario, Canada between May and December 2022. RESULTS: Limited capacity for continuity and comprehensiveness of care were identified as major sources of professional tension for walk-in physicians. Divergent perspectives on their roles were anchored in how physicians viewed their professional identity. Some saw providing continuous and comprehensive care as an infringement on their professional role; others saw their professional role as more flexible and responsive to population needs. Regardless of their professional identity, participants reported feeling ill-equipped to manage the swell of unattached patients, citing a lack of time, resources, connectivity to the system, and remuneration flexibility. Conclusions: As practice demands of walk-in clinics change, an evolution in the professional roles and responsibilities of walk-in physicians follows. However, the resources, structure, and incentives of walk-in care have not evolved to reflect this, leaving physicians to set their own professional boundaries with patients. This results in increasing variations in care and confusion across the primary care sector around who is responsible for what, when, and how.

Rational Design of a Highly Sensitive Carboxylesterase Probe and Its Application in High-Throughput Screening for Uncovering Carboxylesterase Inhibitors.

Tracking carboxylesterases (CESs) through noninvasive and dynamic imaging is of great significance for diagnosing and treating CES-related metabolic diseases. Herein, three BODIPY-based fluorescent probes with a pyridine unit quaternarized via an acetoxybenzyl group were designed and synthesized to detect CESs based on the photoinduced electron transfer process. Notably, among these probes, BDPN2-CES exhibited a remarkable 182-fold fluorescence enhancement for CESs within 10 min. Moreover, BDPN2-CES successfully enabled real-time imaging of endogenous CES variations in living cells. Using BDPN2-CES, a visual high-throughput screening method for CES inhibitors was established, culminating in the discovery of an efficient inhibitor, WZU-13, sourced from a chemical library. These findings suggest that BDPN2-CES could provide a new avenue for diagnosing CES-related diseases, and WZU-13 emerges as a promising therapeutic candidate for CES-overexpression pathological processes.

Efficient EPID-based quality assurance of beam time delay for respiratory-gated radiotherapy with validation on Catalyst™ and AlignRT™ systems.

PURPOSE: To propose a straightforward and time-efficient quality assurance (QA) approach of beam time delay for respiratory-gated radiotherapy and validate the proposed method on typical respiratory gating systems, Catalyst™ and AlignRT™. METHODS: The QA apparatus was composed of a motion platform and a Winston-Lutz cube phantom (WL3) embedded with metal balls. The apparatus was first scanned in CT-Sim and two types of QA plans specific for beam on and beam off time delay, respectively, were designed. Static reference images and motion testing images of the WL3 cube were acquired with EPID. By comparing the position differences of the embedded metal balls in the motion and reference images, beam time delays were determined. The proposed approach was validated on three linacs with either Catalyst™ or AlignRT™ respiratory gating systems. To investigate the impact of energy and dose rate on beam time delay, a range of QA plans with Eclipse (V15.7) were devised with varying energy and dose rates. RESULTS: For all energies, the beam on time delays in AlignRT™ V6.3.226, AlignRT™ V7.1.1, and Catalyst™ were 92.13 ± $ \pm $ 5.79 ms, 123.11 ± $ \pm $ 6.44 ms, and 303.44 ± $ \pm $ 4.28 ms, respectively. The beam off time delays in AlignRT™ V6.3.226, AlignRT™ V7.1.1, and Catalyst™ were 121.87 ± $ \pm $ 1.34 ms, 119.33 ± $ \pm $ 0.75 ms, and 97.69 ± $ \pm $ 2.02 ms, respectively. Furthermore, the beam on delays decreased slightly as dose rates increased for all gating systems, whereas the beam off delays remained unaffected. CONCLUSIONS: The validation results demonstrate the proposed QA approach of beam time delay for respiratory-gated radiotherapy was both reproducible and time-efficient to practice for institutions to customize accordingly.

The role and future prospects of artificial intelligence algorithms in peptide drug development.

Peptide medications have been more well-known in recent years due to their many benefits, including low side effects, high biological activity, specificity, effectiveness, and so on. Over 100 peptide medications have been introduced to the market to treat a variety of illnesses. Most of these peptide medications are developed on the basis of endogenous peptides or natural peptides, which frequently required expensive, time-consuming, and extensive tests to confirm. As artificial intelligence advances quickly, it is now possible to build machine learning or deep learning models that screen a large number of candidate sequences for therapeutic peptides. Therapeutic peptides, such as those with antibacterial or anticancer properties, have been developed by the application of artificial intelligence algorithms.The process of finding and developing peptide drugs is outlined in this review, along with a few related cases that were helped by AI and conventional methods. These resources will open up new avenues for peptide drug development and discovery, helping to meet the pressing needs of clinical patients for disease treatment. Although peptide drugs are a new class of biopharmaceuticals that distinguish them from chemical and small molecule drugs, their clinical purpose and value cannot be ignored. However, the traditional peptide drug research and development has a long development cycle and high investment, and the creation of peptide medications will be substantially hastened by the AI-assisted (AI+) mode, offering a new boost for combating diseases.

SATB1, senescence and senescence-related diseases.

Aging leads to an accumulation of cellular mutations and damage, increasing the risk of senescence, apoptosis, and malignant transformation. Cellular senescence, which is pivotal in aging, acts as both a guard against cellular transformation and as a check against cancer progression. It is marked by stable cell cycle arrest, widespread macromolecular changes, a pro-inflammatory profile, and altered gene expression. However, it remains to be determined whether these differing subsets of senescent cells result from unique intrinsic programs or are influenced by their environmental contexts. Multiple transcription regulators and chromatin modifiers contribute to these alterations. Special AT-rich sequence-binding protein 1 (SATB1) stands out as a crucial regulator in this process, orchestrating gene expression by structuring chromatin into loop domains and anchoring DNA elements. This review provides an overview of cellular senescence and delves into the role of SATB1 in senescence-related diseases. It highlights SATB1's potential in developing antiaging and anticancer strategies, potentially contributing to improved quality of life and addressing aging-related diseases.

MTH1 inhibition synergizes with ROS-inducing agents to trigger cervical cancer cells undergoing parthanatos.

Cervical cancer cells possess high levels of reactive oxygen species (ROS); thus, increasing oxidative stress above the toxicity threshold to induce cell death is a promising chemotherapeutic strategy. However, the underlying mechanisms of cell death are elusive, and efficacy and toxicity issues remain. Within DNA, 8-oxo-7,8-dihydroguanine (8-oxoG) is the most frequent base lesion repaired by 8-oxoguanine glycosylase 1 (OGG1)-initiated base excision repair. Cancer cells also express high levels of MutT homolog 1 (MTH1), which prevents DNA replication-induced incorporation of 8-oxoG into the genome by hydrolyzing 8-oxo-7,8-dihydro-2'-deoxyguanosine 5'-triphosphate (8-oxo-dGTP). Here, we revealed that ROS-inducing agents triggered cervical cancer to undergo parthanatos, which was mainly induced by massive DNA strand breaks resulting from overwhelming 8-oxoG excision by OGG1. Furthermore, the MTH1 inhibitor synergized with a relatively low dose of ROS-inducing agents by enhancing 8-oxoG loading in the DNA. In vivo, this drug combination suppressed the growth of tumor xenografts, and this inhibitory effect was significantly decreased in the absence of OGG1. Hence, the present study highlights the roles of base repair enzymes in cell death induction and suggests that the combination of lower doses of ROS-inducing agents with MTH1 inhibitors may be a more selective and safer strategy for cervical cancer chemotherapy.

Afamitresgene autoleucel for advanced synovial sarcoma and myxoid round cell liposarcoma (SPEARHEAD-1): an international, open-label, phase 2 trial.

BACKGROUND: Afamitresgene autoleucel (afami-cel) showed acceptable safety and promising efficacy in a phase 1 trial (NCT03132922). The aim of this study was to further evaluate the efficacy of afami-cel for the treatment of patients with HLA-A*02 and MAGE-A4-expressing advanced synovial sarcoma or myxoid round cell liposarcoma. METHODS: SPEARHEAD-1 was an open-label, non-randomised, phase 2 trial done across 23 sites in Canada, the USA, and Europe. The trial included three cohorts, of which the main investigational cohort (cohort 1) is reported here. Cohort 1 included patients with HLA-A*02, aged 16-75 years, with metastatic or unresectable synovial sarcoma or myxoid round cell liposarcoma (confirmed by cytogenetics) expressing MAGE-A4, and who had received at least one previous line of anthracycline-containing or ifosfamide-containing chemotherapy. Patients received a single intravenous dose of afami-cel (transduced dose range 1·0 × 109-10·0 × 109 T cells) after lymphodepletion. The primary endpoint was overall response rate in cohort 1, assessed by a masked independent review committee using Response Evaluation Criteria in Solid Tumours (version 1.1) in the modified intention-to-treat population (all patients who received afami-cel). Adverse events, including those of special interest (cytokine release syndrome, prolonged cytopenia, and neurotoxicity), were monitored and are reported for the modified intention-to-treat population. This trial is registered at ClinicalTrials.gov, NCT04044768; recruitment is closed and follow-up is ongoing for cohorts 1 and 2, and recruitment is open for cohort 3. FINDINGS: Between Dec 17, 2019, and July 27, 2021, 52 patients with cytogenetically confirmed synovial sarcoma (n=44) and myxoid round cell liposarcoma (n=8) were enrolled and received afami-cel in cohort 1. Patients were heavily pre-treated (median three [IQR two to four] previous lines of systemic therapy). Median follow-up time was 32·6 months (IQR 29·4-36·1). Overall response rate was 37% (19 of 52; 95% CI 24-51) overall, 39% (17 of 44; 24-55) for patients with synovial sarcoma, and 25% (two of eight; 3-65) for patients with myxoid round cell liposarcoma. Cytokine release syndrome occurred in 37 (71%) of 52 of patients (one grade 3 event). Cytopenias were the most common grade 3 or worse adverse events (lymphopenia in 50 [96%], neutropenia 44 [85%], leukopenia 42 [81%] of 52 patients). No treatment-related deaths occurred. INTERPRETATION: Afami-cel treatment resulted in durable responses in heavily pre-treated patients with HLA-A*02 and MAGE-A4-expressing synovial sarcoma. This study shows that T-cell receptor therapy can be used to effectively target solid tumours and provides rationale to expand this approach to other solid malignancies. FUNDING: Adaptimmune.

Distinct correlation network of clinical characteristics in suicide attempters having adolescent major depressive disorder with non-suicidal self-injury.

Suicidal behavior and non-suicidal self-injury (NSSI) are common in adolescent patients with major depressive disorder (MDD). Thus, delineating the unique characteristics of suicide attempters having adolescent MDD with NSSI is important for suicide prediction in the clinical setting. Here, we performed psychological and biochemical assessments of 130 youths having MDD with NSSI. Participants were divided into two groups according to the presence/absence of suicide attempts (SAs). Our results demonstrated that the age of suicide attempters is lower than that of non-attempters in participants having adolescent MDD with NSSI; suicide attempters had higher Barratt Impulsiveness Scale (BIS-11) impulsivity scores and lower serum CRP and cortisol levels than those having MDD with NSSI alone, suggesting levels of cortisol and CRP were inversely correlated with SAs in patients with adolescent MDD with NSSI. Furthermore, multivariate regression analysis revealed that NSSI frequency in the last month and CRP levels were suicidal ideation predictors in adolescent MDD with NSSI, which may indicate that the increased frequency of NSSI behavior is a potential risk factor for suicide. Additionally, we explored the correlation between psychological and blood biochemical indicators to distinguish suicide attempters among participants having adolescent MDD with NSSI and identified a unique correlation network that could serve as a marker for suicide attempters. Our research data further suggested a complex correlation between the psychological and behavioral indicators of impulsivity and anger. Therefore, our study findings may provide clues to identify good clinical warning signs for SA in patients with adolescent MDD with NSSI.

Bioactive polyketides and meroterpenoids from the mangrove-derived fungus Talaromyces flavus TGGP35.

Six new polyketides, which includes three new lactones (talarotones A-C) (1-3), one new polyketide (talarotide A) (4), two new polyenes (talaroyenes A, B) (5, 6), together with one new meroterpenoid (talaropenoid A) (7) and 13 known compounds (8-20) were isolated from the mangrove-derived fungus Talaromyces flavus TGGP35. The structure and configuration of the compounds 1-7 were elucidated from the data obtained from HR-ESI-MS, IR, 1D/2D NMR spectroscopy, Mo2 (OAc)4-induced electronic circular dichroism (ECD), CD spectroscopy, and modified Mosher's method. Compounds 5 and 20 displayed antioxidant activity with IC50 values of 0.40 and 1.36 mM, respectively. Compounds 3, 6, 11, 16, and 17 displayed cytotoxic activity against human cancer cells Hela, A549, and had IC50 values ranging from 28.89 to 62.23 µM. Compounds 7, 10-12, and 14-18 exhibited moderate or potent anti-insect activity against newly hatched larvae of Helicoverpa armigera Hubner, with IC50 values in the range 50-200 µg/mL. Compound 18 showed antibacterial activity against Ralstonia solanacearum with the MIC value of 50 µg/mL.

Deep learning-based projection synthesis for low-dose cone-beam computed tomography imaging in image-guided radiotherapy.

Background: The imaging dose of cone-beam computed tomography (CBCT) in image-guided radiotherapy (IGRT) poses adverse effects on patient health. To improve the quality of sparse-view low-dose CBCT images, a projection synthesis convolutional neural network (SynCNN) model is proposed. Methods: Included in this retrospective, single-center study were 223 patients diagnosed with brain tumours from Beijing Cancer Hospital. The proposed SynCNN model estimated two pairs of orthogonally direction-separable spatial kernels to synthesize the missing projection in between the input neighboring sparse-view projections via local convolution operations. The SynCNN model was trained on 150 real patients to learn patterns for inter-view projection synthesis. CBCT data from 30 real patients were used to validate the SynCNN, while data from a phantom and 43 real patients were used to test the SynCNN externally. Sparse-view projection datasets with 1/2, 1/4, and 1/8 of the original sampling rate were simulated, and the corresponding full-view projection datasets were restored using the SynCNN model. The tomographic images were then reconstructed with the Feldkamp-Davis-Kress algorithm. The root-mean-square error (RMSE), peak signal-to-noise ratio (PSNR), and structural similarity (SSIM) metrics were measured in both the projection and image domains. Five experts were invited to grade the image quality blindly for 40 randomly selected evaluation groups with a four-level rubric, where a score greater than or equal to 2 was considered acceptable image quality. The running time of the SynCNN model was recorded. The SynCNN model was directly compared with the three other methods on 1/4 sparse-view reconstructions. Results: The phantom and patient studies showed that the missing projections were accurately synthesized. In the image domain, for the phantom study, compared with images reconstructed from sparse-view projections, images with SynCNN synthesis exhibited significantly improved qualities with decreased values in RMSE and increased values in PSNR and SSIM. For the patient study, between the results with and without the SynCNN synthesis, the averaged RMSE decreased by 3.4×10-4, 10.3×10-4, and 21.7×10-4, the averaged PSNR increased by 3.4, 6.6, and 9.4 dB, and the averaged SSIM increased by 5.2×10-2, 18.9×10-2 and 33.9×10-2, for the 1/2, 1/4, and 1/8 sparse-view reconstructions, respectively. In expert subjective evaluation, both the median scores and acceptance rates of the images with SynCNN synthesis were higher than those reconstructed from sparse-view projections. It took the model less than 0.01 s to synthesize an inter-view projection. Compared with the three other methods, the SynCNN model obtained the best scores in terms of the three metrics in both domains. Conclusions: The proposed SynCNN model effectively improves the quality of sparse-view CBCT images at a low time cost. With the SynCNN model, the CBCT imaging dose in IGRT could be reduced potentially.

Microalgae-Based Hydrogel for Inflammatory Bowel Disease and Its Associated Anxiety and Depression.

Patients diagnosed with inflammatory bowel disease (IBD) exhibit a notable prevalence of psychiatric disorders, such as anxiety and depression. Nevertheless, the etiology of psychiatric disorders associated with IBD remains uncertain, and an efficacious treatment approach has yet to be established. Herein, an oral hydrogel strategy (SP@Rh-gel) is proposed for co-delivery of Spirulina platensis and rhein to treat IBD and IBD-associated anxiety and depression by modulating the microbiota-gut-brain axis. SP@Rh-gel improves the solubility, release characteristics and intestinal retention capacity of the drug, leading to a significant improvement in the oral therapeutic efficacy. Oral administration of SP@Rh-gel can reduce intestinal inflammation and rebalance the disrupted intestinal microbial community. Furthermore, SP@Rh-gel maintains intestinal barrier integrity and reduces the release of pro-inflammatory factors and their entry into the hippocampus through the blood-brain barrier, thereby inhibiting neuroinflammation and maintaining neuroplasticity. SP@Rh-gel significantly alleviates the colitis symptoms, as well as anxiety- and depression-like behaviors, in a chronic colitis mouse model. This study demonstrates the significant involvement of the microbiota-gut-brain axis in the development of IBD with psychiatric disorders and proposes a safe, simple, and highly efficient therapeutic approach for managing IBD and comorbid psychiatric disorders.

Conventional and multi-omics assessments of subacute inhalation toxicity due to propylene glycol and vegetable glycerin aerosol produced by electronic cigarettes.

Propylene glycol (PG) and vegetable glycerin (VG) are the most common solvents used in electronic cigarette liquids. No long-term inhalation toxicity assessments have been performed combining conventional and multi-omics approaches on the potential respiratory effects of the solvents in vivo. In this study, the systemic toxicity of aerosol generated from a ceramic heating coil-based e-cigarette was evaluated. First, the aerosol properties were characterized, including carbonyl emissions, the particle size distribution, and aerosol temperatures. To determine toxicological effects, rats were exposed, through their nose only, to filtered air or a propylene glycol (PG)/ glycerin (VG) (50:50, %W/W) aerosol mixture at the target concentration of 3 mg/L for six hours daily over a continuous 28-day period. Compared with the air group, female rats in the PG/VG group exhibited significantly lower body weights during both the exposure period and recovery period, and this was linked to a reduced food intake. Male rats in the PG/VG group also experienced a significant decline in body weight during the exposure period. Importantly, rats exposed to the PG/VG aerosol showed only minimal biological effects compared to those with only air exposure, with no signs of toxicity. Moreover, the transcriptomic, proteomic, and metabolomic analyses of the rat lung tissues following aerosol exposure revealed a series of candidate pathways linking aerosol inhalation to altered lung functions, especially the inflammatory response and disease. Dysregulated pathways of arachidonic acids, the neuroactive ligand-receptor interaction, and the hematopoietic cell lineage were revealed through integrated multi-omics analysis. Therefore, our integrated multi-omics approach offers novel systemic insights and early evidence of environmental-related health hazards associated with an e-cigarette aerosol using two carrier solvents in a rat model.

Doxorubicin-Loaded Microalgal Delivery System for Combined Chemotherapy and Enhanced Photodynamic Therapy of Osteosarcoma.

Osteosarcoma (OS) is considered the most frequent type of primary malignant bone tumor. Currently, radiotherapy, photodynamic (PDT), and other therapies for osteosarcoma are limited by tumor hypoxia and single efficacy and serve side-effects. Herein, we reported a microalgal drug delivery system (SpiD), doxorubicin (DOX)-loaded Spirulina platensis (Spi) for OS therapy. The specific surface of Spirulina platensis allowed for effective loading of DOX via surface channels and electrostatic interactions. Under 650 nm laser irradiation, SpiD enabled high oxygen production by photosynthesis and enhanced reactive oxygen species (ROS) generation via chlorophyll-assisted photosensitization, synergistically killing tumor cells with the released DOX. Combined chemotherapy and enhanced PDT mediated by SpiD exerted synergic antitumor effects and resulted in potent therapeutic efficacy in orthotopic osteosarcoma mice. Furthermore, SpiD could reduce the side-effects of chemotherapy, showing excellent blood and tissue safety. Taken together, this microalgal drug delivery system provided a natural, efficient, safe, and inexpensive strategy for OS treatment.

Homologous chromosome pairing: The linchpin of accurate segregation in meiosis.

Meiosis is a specialized cell division that occurs in sexually reproducing organisms, generating haploid gametes containing half the chromosome number through two rounds of cell division. Homologous chromosomes pair and prepare for their proper segregation in subsequent divisions. How homologous chromosomes recognize each other and achieve pairing is an important question. Early studies showed that in most organisms, homologous pairing relies on homologous recombination. However, pairing mechanisms differ across species. Evidence indicates that chromosomes are dynamic and move during early meiotic stages, facilitating pairing. Recent studies in various model organisms suggest conserved mechanisms and key regulators of homologous chromosome pairing. This review summarizes these findings and compare similarities and differences in homologous chromosome pairing mechanisms across species.