A primer on the use of machine learning to distil knowledge from data in biological psychiatry.

Applications of machine learning in the biomedical sciences are growing rapidly. This growth has been spurred by diverse cross-institutional and interdisciplinary collaborations, public availability of large datasets, an increase in the accessibility of analytic routines, and the availability of powerful computing resources. With this increased access and exposure to machine learning comes a responsibility for education and a deeper understanding of its bases and bounds, borne equally by data scientists seeking to ply their analytic wares in medical research and by biomedical scientists seeking to harness such methods to glean knowledge from data. This article provides an accessible and critical review of machine learning for a biomedically informed audience, as well as its applications in psychiatry. The review covers definitions and expositions of commonly used machine learning methods, and historical trends of their use in psychiatry. We also provide a set of standards, namely Guidelines for REporting Machine Learning Investigations in Neuropsychiatry (GREMLIN), for designing and reporting studies that use machine learning as a primary data-analysis approach. Lastly, we propose the establishment of the Machine Learning in Psychiatry (MLPsych) Consortium, enumerate its objectives, and identify areas of opportunity for future applications of machine learning in biological psychiatry. This review serves as a cautiously optimistic primer on machine learning for those on the precipice as they prepare to dive into the field, either as methodological practitioners or well-informed consumers.

USP13 ameliorates nonalcoholic fatty liver disease through inhibiting the activation of TAK1.

BACKGROUND: The molecular mechanisms underlying nonalcoholic fatty liver disease (NAFLD) remain to be fully elucidated. Ubiquitin specific protease 13 (USP13) is a critical participant in inflammation-related signaling pathways, which are linked to NAFLD. Herein, the roles of USP13 in NAFLD and the underlying mechanisms were investigated. METHODS: L02 cells and mouse primary hepatocytes were subjected to free fatty acid (FFA) to establish an in vitro model reflective of NAFLD. To prepare in vivo model of NAFLD, mice fed a high-fat diet (HFD) for 16 weeks and leptin-deficient (ob/ob) mice were used. USP13 overexpression and knockout (KO) strategies were employed to study the function of USP13 in NAFLD in mice. RESULTS: The expression of USP13 was markedly decreased in both in vitro and in vivo models of NAFLD. USP13 overexpression evidently inhibited lipid accumulation and inflammation in FFA-treated L02 cells in vitro. Consistently, the in vivo experiments showed that USP13 overexpression ameliorated hepatic steatosis and metabolic disorders in HFD-fed mice, while its deficiency led to contrary outcomes. Additionally, inflammation was similarly attenuated by USP13 overexpression and aggravated by its deficiency in HFD-fed mice. Notably, overexpressing of USP13 also markedly alleviated hepatic steatosis and inflammation in ob/ob mice. Mechanistically, USP13 bound to transforming growth factor ß-activated kinase 1 (TAK1) and inhibited K63 ubiquitination and phosphorylation of TAK1, thereby dampening downstream inflammatory pathways and promoting insulin signaling pathways. Inhibition of TAK1 activation reversed the exacerbation of NAFLD caused by USP13 deficiency in mice. CONCLUSIONS: Our findings indicate the protective role of USP13 in NAFLD progression through its interaction with TAK1 and inhibition the ubiquitination and phosphorylation of TAK1. Targeting the USP13-TAK1 axis emerges as a promising therapeutic strategy for NAFLD treatment.

Optical mode manipulation using deep spatial diffractive neural networks.

In this paper, we investigate the theoretical models and potential applications of spatial diffractive neural network (SDNN) structures, with a particular focus on mode manipulation. Our research introduces a novel diffractive transmission simulation method that employs matrix multiplication, alongside a parameter optimization algorithm based on neural network gradient descent. This approach facilitates a comprehensive understanding of the light field manipulation capabilities inherent to SDNNs. We extend our investigation to parameter optimization for SDNNs of various scales. We achieve the demultiplexing of 5, 11 and 100 orthogonal orbital angular momentum (OAM) modes using neural networks with 4, 10 and 50 layers, respectively. Notably, the optimized 100 OAM mode demultiplexer shows an average loss of 0.52 dB, a maximum loss of 0.62 dB, and a maximum crosstalk of -28.24 dB. Further exploring the potential of SDNNs, we optimize a 10-layer structure for mode conversion applications. This optimization enables conversions from Hermite-Gaussian (HG) to Laguerre-Gaussian (LG) modes, as well as from HG to OAM modes, showing the versatility of SDNNs in mode manipulation. We propose an innovative assembly of SDNNs on a glass substrate integrated with photonic devices. A 10-layer diffractive neural network, with a size of 49 mm × 7 mm × 7 mm, effectively demultiplexes 11 orthogonal OAM modes with minimal loss and crosstalk. Similarly, a 20-layer diffractive neural network, with a size of 67 mm × 7 mm × 7 mm, serves as a highly efficient 25-channel OAM to HG mode converter, showing the potential of SDNNs in advanced optical communications.

Clonal evolution from B-cell acute lymphoblastic leukemia with BCR::ABL1 multilineage involvement to acute myeloid leukemia after multiple anti-CD19 chimeric antigen receptor T-cell therapy.

Not available.

Observation of Chiral Symmetry Breaking in Toroidal Vortices of Light.

In this Letter, we explore the intersection of chirality and recently discovered toroidal spatiotemporal optical vortices (STOVs). We introduce "photonic conchs" theoretically as a new type of toroidal-like state exhibiting geometrical chirality, and experimentally observe these wave packets with controllable topological charges. Unlike toroidal STOVs, photonic conchs exhibit unique chirality-related dynamical evolution in free space and possess an orbital angular momentum correlated with all the dimensions of space-time. This research deepens our understanding of toroidal light states and potentially advances various fields by unveiling similar wave phenomena in a broader scope of physics systems, including acoustics and electronics.

Genetic and clinical characteristics of acute B-cell lymphoblastic leukemia with MEF2D fusions and report of two novel MEF2D rearrangements.

The MEF2D rearrangement is a recurrent chromosomal abnormality detected in approximately 2.4-5.3% of patients with acute B-cell lymphoblastic leukemia (B-ALL). Currently, MEF2D-rearranged B-ALL is not classified as an independent subtype in the WHO classification. Consequently, the clinical significance of MEF2D rearrangement in B-ALL remains largely unexplored. In this study, we retrospectively screened 260 B-ALL patients with RNA sequencing data collected between November 2018 and December 2022. Among these, 10 patients were identified with MEF2D rearrangements (4 with MEF2D::HNRNPUL1, 3 with MEF2D::BCL9, 1 with MEF2D::ARID1B, 1 with MEF2D::DAZAP1 and 1 with MEF2D::HNRNPM). Notably, HNRNPM and ARID1B are reported as MEF2D fusion partners for the first time. The patient with the MEF2D::HNRNPM fusion was resistant to chemotherapy and chimeric antigen receptor T-cell therapy and relapsed early after allogenic stem cell transplantation. The patient with MEF2D::ARID1B experienced early extramedullary relapse after diagnosis. All 10 patients achieved complete remission after induction chemotherapy. However, 9/10 (90%) of whom experienced relapse. Three of the 9 patients relapsed with aberrant expression of myeloid antigens. The median overall survival of these patients was only 11 months. This small cohort showed a high incidence of early relapse and short survival in patients with MEF2D rearrangements.

Role of Nitrogenous Functional Group Identity in Accelerating 1,2,3-Trichloropropane Degradation by Pyrogenic Carbonaceous Matter (PCM) and Sulfide Using PCM-like Polymers.

Groundwater contamination by 1,2,3-trichloropropane (TCP) poses a unique challenge due to its human toxicity and recalcitrance to degradation. Previous work suggests that nitrogenous functional groups of pyrogenic carbonaceous matter (PCM), such as biochar, are important in accelerating contaminant dechlorination by sulfide. However, the reaction mechanism is unclear due, in part, to PCM's structural complexity. Herein, PCM-like polymers (PLPs) with controlled placement of nitrogenous functional groups [i.e., quaternary ammonium (QA), pyridine, and pyridinium cations (py+)] were employed as model systems to investigate PCM-enhanced TCP degradation by sulfide. Our results suggest that both PLP-QA and PLP-py+ were highly effective in facilitating TCP dechlorination by sulfide with half-lives of 16.91 ± 1.17 and 0.98 ± 0.15 days, respectively, and the reactivity increased with surface nitrogenous group density. A two-step process was proposed for TCP dechlorination, which is initiated by reductive ß-elimination, followed by nucleophilic substitution by surface-bound sulfur nucleophiles. The TCP degradation kinetics were not significantly affected by cocontaminants (i.e., 1,1,1-trichloroethane or trichloroethylene), but were slowed by natural organic matter. Our results show that PLPs containing certain nitrogen functional groups can facilitate the rapid and complete degradation of TCP by sulfide, suggesting that similarly functionalized PCM might form the basis for a novel process for the remediation of TCP-contaminated groundwater.

Ixekizumab-induced urticaria is associated with the short duration of remission in psoriasis by activation of mast cells.

BACKGROUND: Mast cell degranulation plays a pivotal role in urticaria and is also an early histologic characteristic of psoriasis. However, whether the activation of mast cells contributes to psoriasis recurrence after discontinuation of interleukin (IL)-17A blockers remains unclear. OBJECTIVE: To investigate the role of mast cells in ixekizumab treatment-associated urticaria (ITAUR) and assess the effect of urticaria eruption on psoriasis relapse. METHODS: A retrospective analysis was performed on biopsies of patients who experienced psoriasis relapse after discontinuation of ixekizumab. Transcriptomic and histopathologic features were assessed. Patterns were compared between patients with ITAUR and nonurticaria (NUR) as well as psoriasis-like mice with mast cell activation or inactivation. RESULTS: Patients with ITAUR experienced early relapse compared with NUR group after treatment withdrawal. Transcriptomic and histopathologic analyses revealed that patients with ITAUR had an elevated proportion of mast cells in resolved skin. Especially, the proportion of IL-17A+ mast cells was inversely correlated with the duration of remission. LIMITATIONS: The mechanism of mast cell activation in ITAUR has not been precisely elucidated. CONCLUSION: Ixekizumab treatment increases IL-17A+ mast cells in lesions of ITAUR, which is associated with early psoriasis relapse after ixekizumab withdrawal.

Author Correction: The axolotl genome and the evolution of key tissue formation regulators.

In the originally published version of this Article, the sequenced axolotl strain (the homozygous white mutant) was denoted as 'D/D' rather than 'd/d' in Fig. 1a and the accompanying legend, the main text and the Methods section. The original Article has been corrected online.

The axolotl genome and the evolution of key tissue formation regulators.

Salamanders serve as important tetrapod models for developmental, regeneration and evolutionary studies. An extensive molecular toolkit makes the Mexican axolotl (Ambystoma mexicanum) a key representative salamander for molecular investigations. Here we report the sequencing and assembly of the 32-gigabase-pair axolotl genome using an approach that combined long-read sequencing, optical mapping and development of a new genome assembler (MARVEL). We observed a size expansion of introns and intergenic regions, largely attributable to multiplication of long terminal repeat retroelements. We provide evidence that intron size in developmental genes is under constraint and that species-restricted genes may contribute to limb regeneration. The axolotl genome assembly does not contain the essential developmental gene Pax3. However, mutation of the axolotl Pax3 paralogue Pax7 resulted in an axolotl phenotype that was similar to those seen in Pax3-/- and Pax7-/- mutant mice. The axolotl genome provides a rich biological resource for developmental and evolutionary studies.

Improved reference genome of Aedes aegypti informs arbovirus vector control.

Female Aedes aegypti mosquitoes infect more than 400 million people each year with dangerous viral pathogens including dengue, yellow fever, Zika and chikungunya. Progress in understanding the biology of mosquitoes and developing the tools to fight them has been slowed by the lack of a high-quality genome assembly. Here we combine diverse technologies to produce the markedly improved, fully re-annotated AaegL5 genome assembly, and demonstrate how it accelerates mosquito science. We anchored physical and cytogenetic maps, doubled the number of known chemosensory ionotropic receptors that guide mosquitoes to human hosts and egg-laying sites, provided further insight into the size and composition of the sex-determining M locus, and revealed copy-number variation among glutathione S-transferase genes that are important for insecticide resistance. Using high-resolution quantitative trait locus and population genomic analyses, we mapped new candidates for dengue vector competence and insecticide resistance. AaegL5 will catalyse new biological insights and intervention strategies to fight this deadly disease vector.

Serum lipidomic study of long-chain fatty acids in psoriasis patients prior to and after anti-IL-17A monoclonal antibody treatment by quantitative GC‒MS analysis with in situ extraction.

BACKGROUND: Long-chain fatty acids (LCFAs) are involved in regulating multiple physiological processes as signalling molecules. Gas chromatography-mass spectrometry (GC-MS) is widely used to quantify LCFAs. However, current quantitative methods for LCFAs using GC-MS have demonstrated complicated issues. Psoriasis is a chronic inflammatory skin disease, and its pathogenesis may be related to the overproduction of interleukin-17A (IL-17A). Clinical efficacy of anti-IL-17A monoclonal antibody (mAb) treatment in psoriasis patients has been demonstrated. Recent studies suggest that LCFAs play varying roles in the pathogenesis of psoriasis. However, more comprehensive research is needed to illuminate the mechanism of LCFAs in psoriasis. METHODS: The established in situ derivatization method for analysing LCFAs with a GC-MS platform was utilized to conduct serum lipidomics analysis of healthy volunteers and psoriasis patients receiving pretherapy and posttreatment with of anti-IL-17A mAb. Imiquimod (IMQ)-treated wild type (WT) and T-cell receptor delta chain knock-out (Tcrd-/-) mice were used to investigate the correlation between IL-17A and abnormal changes in LCFAs in psoriasis patients. RESULTS: A rapid and sensitive in situ extraction derivatization method for quantifying LCFAs using GC-MS was established. Serum lipidomic results showed that psoriasis patients had higher levels of saturated fatty acids (SFAs) and ω-6 polyunsaturated fatty acids (PUFAs) but lower levels of monounsaturated fatty acids (MUFAs) and ω-3 PUFAs than healthy individuals, indicating impaired serum LCFA metabolism. Anti-IL-17A mAb treatment affected most of these LCFA changes. Analysis of LCFAs in IMQ-treated mice showed that LCFAs increased in the serum of WT mice, while there were no significant changes in the Tcrd-/- mice. SFAs increased in IMQ-treated WT mice, while MUFAs showed the opposite trend, and PUFAs did not change significantly. CONCLUSIONS: This study presented a dependable method for quantifying LCFAs that enhanced sensitivity and reduced analysis time. The lipidomic analysis results showed that anti-IL-17A mAb not only ameliorated skin lesions in psoriasis patients but also affected abnormal LCFAs metabolism. Furthermore, the study indicated a potential correlation between IL-17A and abnormal LCFA metabolism in psoriasis patients, which was supported by the alterations in serum LCFAs observed in IMQ-treated WT and Tcrd-/- mice.

Using blood transcriptome analysis for Alzheimer's disease diagnosis and patient stratification.

INTRODUCTION: Blood protein biomarkers demonstrate potential for Alzheimer's disease (AD) diagnosis. Limited studies examine the molecular changes in AD blood cells. METHODS: Bulk RNA-sequencing of blood cells was performed on AD patients of Chinese descent (n = 214 and 26 in the discovery and validation cohorts, respectively) with normal controls (n = 208 and 38 in the discovery and validation cohorts, respectively). Weighted gene co-expression network analysis (WGCNA) and deconvolution analysis identified AD-associated gene modules and blood cell types. Regression and unsupervised clustering analysis identified AD-associated genes, gene modules, cell types, and established AD classification models. RESULTS: WGCNA on differentially expressed genes revealed 15 gene modules, with 6 accurately classifying AD (areas under the receiver operating characteristics curve [auROCs] > 0.90). These modules stratified AD patients into subgroups with distinct disease states. Cell-type deconvolution analysis identified specific blood cell types potentially associated with AD pathogenesis. DISCUSSION: This study highlights the potential of blood transcriptome for AD diagnosis, patient stratification, and mechanistic studies. HIGHLIGHTS: We comprehensively analyze the blood transcriptomes of a well-characterized Alzheimer's disease cohort to identify genes, gene modules, pathways, and specific blood cells associated with the disease. Blood transcriptome analysis accurately classifies and stratifies patients with Alzheimer's disease, with some gene modules achieving classification accuracy comparable to that of the plasma ATN biomarkers. Immune-associated pathways and immune cells, such as neutrophils, have potential roles in the pathogenesis and progression of Alzheimer's disease.

ShSPI Inhibits Thrombosis Formation and Ischemic Stroke In Vivo.

Thrombotic diseases, emerging as a global public health hazard with high mortality and disability rates, pose a significant threat to human health and longevity. Although current antithrombotic therapies are effective in treating these conditions, they often carry a substantial risk of bleeding, highlighting the urgent need for safer therapeutic alternatives. Recent evidence has increasingly pointed to a connection between elastase activity and thrombosis. In the current study, we investigated the antithrombotic effects of ShSPI, an elastase inhibitor peptide derived from the venom of Scolopendra hainanum. Results showed that ShSPI significantly attenuated carrageenan-induced thrombosis in vivo. Furthermore, ShSPI effectively inhibited the carrageenan-induced decrease in serum superoxide dismutase (SOD) activity and increase in prothrombin time, fibrinogen level, and endothelial nitric oxide synthase (eNOS) activity. In addition, ShSPI reduced intracerebral thrombosis and improved functional outcomes following ischemic stroke in a transient middle cerebral artery occlusion (tMCAO) mouse model. Collectively, these findings suggest that ShSPI is a promising candidate for the development of novel thrombotic therapies.

Child-Sum EATree-LSTMs: enhanced attentive Child-Sum Tree-LSTMs for biomedical event extraction.

BACKGROUND: Tree-structured neural networks have shown promise in extracting lexical representations of sentence syntactic structures, particularly in the detection of event triggers using recursive neural networks. METHODS: In this study, we introduce an attention mechanism into Child-Sum Tree-LSTMs for the detection of biomedical event triggers. We incorporate previous researches on assigning attention weights to adjacent nodes and integrate this mechanism into Child-Sum Tree-LSTMs to improve the detection of event trigger words. We also address a limitation of shallow syntactic dependencies in Child-Sum Tree-LSTMs by integrating deep syntactic dependencies to enhance the effect of the attention mechanism. RESULTS: Our proposed model, which integrates an enhanced attention mechanism into Tree-LSTM, shows the best performance for the MLEE and BioNLP'09 datasets. Moreover, our model outperforms almost all complex event categories for the BioNLP'09/11/13 test set. CONCLUSION: We evaluate the performance of our proposed model with the MLEE and BioNLP datasets and demonstrate the advantage of an enhanced attention mechanism in detecting biomedical event trigger words.

dsMTL: a computational framework for privacy-preserving, distributed multi-task machine learning.

MOTIVATION: In multi-cohort machine learning studies, it is critical to differentiate between effects that are reproducible across cohorts and those that are cohort-specific. Multi-task learning (MTL) is a machine learning approach that facilitates this differentiation through the simultaneous learning of prediction tasks across cohorts. Since multi-cohort data can often not be combined into a single storage solution, there would be the substantial utility of an MTL application for geographically distributed data sources. RESULTS: Here, we describe the development of 'dsMTL', a computational framework for privacy-preserving, distributed multi-task machine learning that includes three supervised and one unsupervised algorithms. First, we derive the theoretical properties of these methods and the relevant machine learning workflows to ensure the validity of the software implementation. Second, we implement dsMTL as a library for the R programming language, building on the DataSHIELD platform that supports the federated analysis of sensitive individual-level data. Third, we demonstrate the applicability of dsMTL for comorbidity modeling in distributed data. We show that comorbidity modeling using dsMTL outperformed conventional, federated machine learning, as well as the aggregation of multiple models built on the distributed datasets individually. The application of dsMTL was computationally efficient and highly scalable when applied to moderate-size (n < 500), real expression data given the actual network latency. AVAILABILITY AND IMPLEMENTATION: dsMTL is freely available at https://github.com/transbioZI/dsMTLBase (server-side package) and https://github.com/transbioZI/dsMTLClient (client-side package). SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Pretreatment with 3-methyladenine ameliorated Pseudomonas aeruginosa-induced acute pneumonia by inhibiting cell death of neutrophils in a mouse infection model.

Pseudomonas aeruginosa is one of the leading causes of nosocomial infections worldwide. Clinical isolates that are resistant to multiple antimicrobials make it intractable. The interactions between P. aeruginosa and host cell death have multiple effects on bacterial clearance and inflammation; however, the potential intervention effects remain to be defined. Herein, we demonstrated that intravenous administration of 3-methyladenine before, but not after, P. aeruginosa infection enhanced autophagy-independent survival, which was accompanied by a decrease in the bacterial load, alleviation of pathology and reduction in inflammatory cytokines, in an acute pneumonia mouse model. Interestingly, these beneficial effects were not dependent on neutrophil recruitment or phagocytosis, but on the enhanced killing capacity induced by inhibiting the cell death of 3-MA pretreated neutrophils. These findings demonstrate a novel protective role of 3-MA pretreatment in P. aeruginosa-induced acute pneumonia.

Genome-wide comparison of DNA methylation patterns between yak and three cattle strains and their potential association with mRNA transcription.

Yak has evolved specific adaptative mechanisms to high-altitude environment. Up to date, only a few studies reported the DNA methylation in yak. In the present study, genome-wide DNA methylome and transcriptome profiles in lung, mammary, and biceps brachii muscle tissues were compared between yak and three cattle breeds (Tibetan cattle, Sanjiang cattle, and Holstein cattle). The association between differentially expressed genes (DEGs) and differentially methylated regions (DMRs) was analyzed, and the biological functions of DEGs potentially driven by DMRs were explored by KEGG enrichment analysis. Finally, we found that yak-specific DMRs-driven DEGs were mainly involved in neuromodulation, respiration, lung development, blood pressure regulation, cardiovascular protection, energy metabolism, DNA repair, and immune functions. The higher levels of the key genes associated with these functions were observed in yak than in cattle, suggesting that DNA methylation might regulate these genes. Overall, the present study contributes basic data at the DNA methylation level to further understand the physiological metabolism in yak.

All-fiber function devices for twisted lights.

Lights carrying orbital angular momentum (OAM), also called twisted lights, have been applied in fields of optical manipulation, imaging, quantum communication, and mode-division-multiplexing (MDM) optical communication systems. Traditional approaches for manipulating twisted lights carrying OAM in free space paths such as Q-plates, spiral phase plates (SPPs), and spatial light modulators (SLMs) that are usually affected by diffraction effect and imperfect alignment between different optical components, limiting the practical applications of twisted lights. Here we design, fabricated, and package all-fiber function devices for twisted light carrying OAM such as all-fiber broadband OAM generator, all-fiber OAM (de)multiplexer, all-fiber OAM & WDM coupler, and all-fiber OAM 1 × 2 coupler. Base on coupled mode theory and phase-matching condition, twisted light can be generated and detected by pre-tapered single mode fiber (SMF) fusing with multi-mode fiber (MMF). The results show that the proposed all-fiber function devices for twist light have large working broadband (at least C band), high purity (above 95%), and low insert loss (less than 3 dB). The proposed devices will open a reliable way for twisted light applied in optical fiber communications and optical interconnections.

Robust optical edge detection enabled by a twisted reflective q-plate.

Optical edge detection significantly reduces the image information load and is highly sought after in instant image processing. Robustness to the wavelength and polarization of light as well as mechanical vibration is a key requirement for practical applications. Here, a robust optical edge detector is proposed and demonstrated based on a reflective twisted liquid crystal q-plate. The device is composed of a mirror and a 1.46-µm-thick liquid crystal layer with a twist angle of 69.2°. The backtracking of the light inside the twisted medium forms a mirror symmetric twisted design and thus leads to a broadband self-compensated spiral phase modulation. By this means, an optical edge detector with excellent wavelength and polarization independence is presented for both coherent and partially coherent light sources. Additionally, the reflective design makes the system more compact and stable. This work supplies a practical design for robust optical edge detection, which may upgrade existing image processing techniques.