Factors associated with pathological complete remission after neoadjuvant chemoradiotherapy in locally advanced rectal cancer: a real-world clinical setting

ObjectiveThis study aims to identify factors associated with achieving a pathological complete remission (pCR) in patients with locally advanced rectal cancer (LARC) after neoadjuvant chemoradiotherapy (nCRT).MethodsWe conducted a cohort analysis of 171 LARC patients who underwent curative resection post-nCRT at the First Affiliated Hospital of Guangxi Medical University between January 2015 and December 2021. The data encompassed clinical and pathological information. Univariate and binary logistic regression multivariate analyses were employed to examine the factors influencing pCR achievement after nCRT. Kappa value tests were utilized to compare clinical staging after nCRT with postoperative pathological staging.ResultsPostoperative histopathology revealed that of the 171 patients, 40 (23.4%) achieved TRG 0 grade (pCR group), while 131 (76.6%) did not achieve pCR, comprising 36 TRG1, 42 TRG2, and 53 TRG3 cases. Univariate analysis indicated that younger age (p=0.008), reduced tumor occupation of intestinal circumference (p =0.008), specific pathological types (p=0.011), and lower pre-nCRT CEA levels (p=0.003) correlated with pCR attainment. Multivariate analysis identified these factors as independent predictors of pCR: younger age (OR=0.946, p=0.004), smaller tumor occupation of intestinal circumference (OR=2.809, p=0.046), non-mucinous adenocarcinoma pathological type (OR=10.405, p=0.029), and lower pre-nCRT serum CEA levels (OR=2.463, p=0.031). Clinical re-staging post-nCRT compared to postoperative pathological staging showed inconsistent MRI T staging (Kappa=0.012, p=0.718, consistency rate: 35.1%) and marginally consistent MRI N staging (Kappa=0.205, p=0.001, consistency rate: 59.6%).ConclusionLARC patients with younger age, presenting with smaller tumor circumferences in the intestinal lumen, lower pre-nCRT serum CEA levels, and non-mucinous adenocarcinoma are more likely to achieve pCR after nCRT. The study highlights the need for improved accuracy in clinical re-staging assessments after nCRT in LARC

Functional connectivity changes are correlated with sleep improvement in chronic insomnia patients after rTMS treatment

BackgroundRepetitive transcranial magnetic stimulation (rTMS) has been increasingly used as a treatment modality for chronic insomnia disorder (CID). However, our understanding of the mechanisms underlying the efficacy of rTMS is limited.ObjectiveThis study aimed to investigate rTMS-induced alterations in resting-state functional connectivity and to find potential connectivity biomarkers for predicting and tracking clinical outcomes after rTMS.MethodsThirty-seven patients with CID received a 10-session low frequency rTMS treatment applied to the right dorsolateral prefrontal cortex. Before and after treatment, the patients underwent resting-state electroencephalography recordings and a sleep quality assessment using the Pittsburgh Sleep Quality Index (PSQI).ResultsAfter treatment, rTMS significantly increased the connectivity of 34 connectomes in the lower alpha frequency band (8–10 Hz). Additionally, alterations in functional connectivity between the left insula and the left inferior eye junction, as well as between the left insula and medial prefrontal cortex, were associated with a decrease in PSQI score. Further, the correlation between the functional connectivity and PSQI persisted 1 month after the completion of rTMS as evidenced by subsequent electroencephalography (EEG) recordings and the PSQI assessment.ConclusionBased on these results, we established a link between alterations in functional connectivity and clinical outcomes of rTMS, which suggested that EEG-derived functional connectivity changes were associated with clinical improvement of rTMS in treating CID. These findings provide preliminary evidence that rTMS may improve insomnia symptoms by modifying functional connectivity, which can be used to inform prospective clinical trials and potentially for treatment optimization

Comparative cellular analysis of motor cortex in human, marmoset and mouse

The primary motor cortex (M1) is essential for voluntary fine-motor control and is functionally conserved across mammals1. Here, using high-throughput transcriptomic and epigenomic profiling of more than 450,000 single nuclei in humans, marmoset monkeys and mice, we demonstrate a broadly conserved cellular makeup of this region, with similarities that mirror evolutionary distance and are consistent between the transcriptome and epigenome. The core conserved molecular identities of neuronal and non-neuronal cell types allow us to generate a cross-species consensus classification of cell types, and to infer conserved properties of cell types across species. Despite the overall conservation, however, many species-dependent specializations are apparent, including differences in cell-type proportions, gene expression, DNA methylation and chromatin state. Few cell-type marker genes are conserved across species, revealing a short list of candidate genes and regulatory mechanisms that are responsible for conserved features of homologous cell types, such as the GABAergic chandelier cells. This consensus transcriptomic classification allows us to use patch-seq (a combination of whole-cell patch-clamp recordings, RNA sequencing and morphological characterization) to identify corticospinal Betz cells from layer 5 in non-human primates and humans, and to characterize their highly specialized physiology and anatomy. These findings highlight the robust molecular underpinnings of cell-type diversity in M1 across mammals, and point to the genes and regulatory pathways responsible for the functional identity of cell types and their species-specific adaptations

A multimodal cell census and atlas of the mammalian primary motor cortex

ABSTRACT We report the generation of a multimodal cell census and atlas of the mammalian primary motor cortex (MOp or M1) as the initial product of the BRAIN Initiative Cell Census Network (BICCN). This was achieved by coordinated large-scale analyses of single-cell transcriptomes, chromatin accessibility, DNA methylomes, spatially resolved single-cell transcriptomes, morphological and electrophysiological properties, and cellular resolution input-output mapping, integrated through cross-modal computational analysis. Together, our results advance the collective knowledge and understanding of brain cell type organization: First, our study reveals a unified molecular genetic landscape of cortical cell types that congruently integrates their transcriptome, open chromatin and DNA methylation maps. Second, cross-species analysis achieves a unified taxonomy of transcriptomic types and their hierarchical organization that are conserved from mouse to marmoset and human. Third, cross-modal analysis provides compelling evidence for the epigenomic, transcriptomic, and gene regulatory basis of neuronal phenotypes such as their physiological and anatomical properties, demonstrating the biological validity and genomic underpinning of neuron types and subtypes. Fourth, in situ single-cell transcriptomics provides a spatially-resolved cell type atlas of the motor cortex. Fifth, integrated transcriptomic, epigenomic and anatomical analyses reveal the correspondence between neural circuits and transcriptomic cell types. We further present an extensive genetic toolset for targeting and fate mapping glutamatergic projection neuron types toward linking their developmental trajectory to their circuit function. Together, our results establish a unified and mechanistic framework of neuronal cell type organization that integrates multi-layered molecular genetic and spatial information with multi-faceted phenotypic properties

Predicting response to repetitive transcranial magnetic stimulation in patients with chronic insomnia disorder using electroencephalography: A pilot study

Predicting responsvienss to repetitive transcranial magnetic stimulation (rTMS) can facilitate personalized treatments with improved efficacy; however, predictive features related to this response are still lacking. We explored whether resting-state electroencephalography (rsEEG) functional connectivity measured at baseline or during treatment could predict the response to 10-day rTMS targeted to the right dorsolateral prefrontal cortex (DLPFC) in 36 patients with chronic insomnia disorder (CID). Pre- and post-treatment rsEEG scans and the Pittsburgh Sleep Quality Index (PSQI) were evaluated, with an additional rsEEG scan conducted after four rTMS sessions. Machine-learning approaches were employed to assess the ability of each connectivity measure to distinguish between responders (PSQI improvement > 25%) and non-responders (PSQI improvement ≤ 25%). Furthermore, we analyzed the connectivity trends of the two subgroups throughout the treatment. Our results revealed that the machine learning model based on baseline theta connectivity achieved the highest accuracy (AUC = 0.843) in predicting treatment response. Decreased baseline connectivity at the stimulated site was associated with higher responsiveness to TMS, emphasizing the significance of functional connectivity characteristics in rTMS treatment. These findings enhance the clinical application of EEG functional connectivity markers in predicting treatment outcomes

Structural insights into drug transport by an aquaglyceroporin

Abstract Pentamidine and melarsoprol are primary drugs used to treat the lethal human sleeping sickness caused by the parasite Trypanosoma brucei. Cross-resistance to these two drugs has recently been linked to aquaglyceroporin 2 of the trypanosome (TbAQP2). TbAQP2 is the first member of the aquaporin family described as capable of drug transport; however, the underlying mechanism remains unclear. Here, we present cryo-electron microscopy structures of TbAQP2 bound to pentamidine or melarsoprol. Our structural studies, together with the molecular dynamic simulations, reveal the mechanisms shaping substrate specificity and drug permeation. Multiple amino acids in TbAQP2, near the extracellular entrance and inside the pore, create an expanded conducting tunnel, sterically and energetically allowing the permeation of pentamidine and melarsoprol. Our study elucidates the mechanism of drug transport by TbAQP2, providing valuable insights to inform the design of drugs against trypanosomiasis

Functional connectivity changes are correlated with sleep improvement in chronic insomnia patients after rTMS treatment

BackgroundRepetitive transcranial magnetic stimulation (rTMS) has been increasingly used as a treatment modality for chronic insomnia disorder (CID). However, our understanding of the mechanisms underlying the efficacy of rTMS is limited.ObjectiveThis study aimed to investigate rTMS-induced alterations in resting-state functional connectivity and to find potential connectivity biomarkers for predicting and tracking clinical outcomes after rTMS.MethodsThirty-seven patients with CID received a 10-session low frequency rTMS treatment applied to the right dorsolateral prefrontal cortex. Before and after treatment, the patients underwent resting-state electroencephalography recordings and a sleep quality assessment using the Pittsburgh Sleep Quality Index (PSQI).ResultsAfter treatment, rTMS significantly increased the connectivity of 34 connectomes in the lower alpha frequency band (8-10 Hz). Additionally, alterations in functional connectivity between the left insula and the left inferior eye junction, as well as between the left insula and medial prefrontal cortex, were associated with a decrease in PSQI score. Further, the correlation between the functional connectivity and PSQI persisted 1 month after the completion of rTMS as evidenced by subsequent electroencephalography (EEG) recordings and the PSQI assessment.ConclusionBased on these results, we established a link between alterations in functional connectivity and clinical outcomes of rTMS, which suggested that EEG-derived functional connectivity changes were associated with clinical improvement of rTMS in treating CID. These findings provide preliminary evidence that rTMS may improve insomnia symptoms by modifying functional connectivity, which can be used to inform prospective clinical trials and potentially for treatment optimization

Data_Sheet_1_Functional connectivity changes are correlated with sleep improvement in chronic insomnia patients after rTMS treatment.docx

BackgroundRepetitive transcranial magnetic stimulation (rTMS) has been increasingly used as a treatment modality for chronic insomnia disorder (CID). However, our understanding of the mechanisms underlying the efficacy of rTMS is limited.ObjectiveThis study aimed to investigate rTMS-induced alterations in resting-state functional connectivity and to find potential connectivity biomarkers for predicting and tracking clinical outcomes after rTMS.MethodsThirty-seven patients with CID received a 10-session low frequency rTMS treatment applied to the right dorsolateral prefrontal cortex. Before and after treatment, the patients underwent resting-state electroencephalography recordings and a sleep quality assessment using the Pittsburgh Sleep Quality Index (PSQI).ResultsAfter treatment, rTMS significantly increased the connectivity of 34 connectomes in the lower alpha frequency band (8–10 Hz). Additionally, alterations in functional connectivity between the left insula and the left inferior eye junction, as well as between the left insula and medial prefrontal cortex, were associated with a decrease in PSQI score. Further, the correlation between the functional connectivity and PSQI persisted 1 month after the completion of rTMS as evidenced by subsequent electroencephalography (EEG) recordings and the PSQI assessment.ConclusionBased on these results, we established a link between alterations in functional connectivity and clinical outcomes of rTMS, which suggested that EEG-derived functional connectivity changes were associated with clinical improvement of rTMS in treating CID. These findings provide preliminary evidence that rTMS may improve insomnia symptoms by modifying functional connectivity, which can be used to inform prospective clinical trials and potentially for treatment optimization.</p