Two-step reconstruction framework of fluorescence molecular tomography based on energy statistical probability.

Fluorescence molecular tomography (FMT), as a promising technique for early tumor detection, can non-invasively visualize the distribution of fluorescent marker probe three-dimensionally. However, FMT reconstruction is a severely ill-posed problem, which remains an obstacle to wider application of FMT. In this paper, a two-step reconstruction framework was proposed for FMT based on the energy statistical probability. First, the tissue structural information obtained from computed tomography (CT) is employed to associate the tissue optical parameters for rough solution in the global region. Then, according to the global-region reconstruction results, the probability that the target belongs to each region can be calculated. The region with the highest probability is delineated as region of interest to realize accurate and fast source reconstruction. Numerical simulations and in vivo experiments were carried out to evaluate the effectiveness of the proposed framework. The encouraging results demonstrate the significant effectiveness and potential of our method for practical FMT applications.

Interpretable artificial intelligence-based app assists inexperienced radiologists in diagnosing biliary atresia from sonographic gallbladder images.

BACKGROUND: A previously trained deep learning-based smartphone app provides an artificial intelligence solution to help diagnose biliary atresia from sonographic gallbladder images, but it might be impractical to launch it in real clinical settings. This study aimed to redevelop a new model using original sonographic images and their derived smartphone photos and then test the new model's performance in assisting radiologists with different experiences to detect biliary atresia in real-world mimic settings. METHODS: A new model was first trained retrospectively using 3659 original sonographic gallbladder images and their derived 51,226 smartphone photos and tested on 11,410 external validation smartphone photos. Afterward, the new model was tested in 333 prospectively collected sonographic gallbladder videos from 207 infants by 14 inexperienced radiologists (9 juniors and 5 seniors) and 4 experienced pediatric radiologists in real-world mimic settings. Diagnostic performance was expressed as the area under the receiver operating characteristic curve (AUC). RESULTS: The new model outperformed the previously published model in diagnosing BA on the external validation set (AUC 0.924 vs 0.908, P = 0.004) with higher consistency (kappa value 0.708 vs 0.609). When tested in real-world mimic settings using 333 sonographic gallbladder videos, the new model performed comparable to experienced pediatric radiologists (average AUC 0.860 vs 0.876) and outperformed junior radiologists (average AUC 0.838 vs 0.773) and senior radiologists (average AUC 0.829 vs 0.749). Furthermore, the new model could aid both junior and senior radiologists to improve their diagnostic performances, with the average AUC increasing from 0.773 to 0.835 for junior radiologists and from 0.749 to 0.805 for senior radiologists. CONCLUSIONS: The interpretable app-based model showed robust and satisfactory performance in diagnosing biliary atresia, and it could aid radiologists with limited experiences to improve their diagnostic performances in real-world mimic settings.

Improved Short-Chain Fatty Acids Production and Protein Degradation During the Anaerobic Fermentation of Waste-Activated Sludge via Alumina Slag-Modified Biochar.

As the by-product in the biological sewage treatment, waste-activated sludge (WAS) always suffers from the difficulty of disposal. Anaerobic fermentation to achieve valuable carbon sources is a feasible way for resource utilization of WAS, whereas the process is always restricted by its biochemical efficiency. Hence, the WAS was used as the feedstock in this study. Alumina slag-modified biochar (Al@BioC) respectively from pine wood (PW) or fresh vinegar residue (FVR) was employed to stimulate the process of short-chain fatty acids (SCFAs) production during the anaerobic treatment of WAS. The results indicate that the addition of Al@BioC could facilitate the distinct increase in SCFAs yield (42.66 g/L) by 14.09% and acetate yield (33.30 g/L) by 18.77%, respectively, when compared with that in regular fermentation without Al@BioC addition. Furthermore, protein degradation was also improved. With the Al@BioCPW added, the maximum concentration of soluble protein reached 867.68 mg/L and was 24.39% higher than the initial level, while the enhancement in the group with Al@BioCFVR and without biochar addition was 12.49% and 7.44%, respectively. According to the results of 16S rDNA sequencing, the relative abundance of acid-producing bacteria (Bacteroidota and Firmicutes) was enriched, enhancing the pathways of protein metabolisms and the ability to resist the harsh environment, respectively. Moreover, Proteiniphilum under Bacteroidota and Fastidiosipila under Firmicutes were the main microorganisms to metabolize protein. The above results might provide a novel material for harvesting the SCFAs production, which is conducive to harmless disposal and carbon resource recovery.

Regularization parameter based on incomplete variables for X-ray luminescence computed tomography.

X-ray luminescence computed tomography (XLCT) is an emerging molecular imaging technique for biological application. However, it is still a challenge to get a stable and accurate solution of the reconstruction of XLCT. This paper presents a regularization parameter selection strategy based on incomplete variables frame for XLCT. A residual information, which is derived from Karush-Kuhn-Tucker (KKT) equivalent condition, is employed to determine the regularization parameter. This residual contains the relevant information about the solution norm and gradient norm, which improved the recovered results. Simulation and phantom experiments are designed to test the performance of the algorithm.Clinical Relevance- The results have not yet been used in clinical relevance currently, we believed that this strategy will facilitate the development of the preclinical applications in FMT.

Cuproptosis and cuproptosis-related genes: Emerging potential therapeutic targets in breast cancer.

Breast cancer is one of the most common malignant tumors in women worldwide, and thus, it is important to enhance its treatment efficacy [1]. Copper has emerged as a critical trace element that affects various intracellular signaling pathways, gene expression, and biological metabolic processes [2], thereby playing a crucial role in the pathogenesis of breast cancer. Recent studies have identified cuproptosis, a newly discovered type of cell death, as an emerging therapeutic target for breast cancer treatment, thereby offering new hope for breast cancer patients. Tsvetkov's research has elucidated the mechanism of cuproptosis and uncovered the critical genes involved in its regulation [3]. Manipulating the expression of these genes could potentially serve as a promising therapeutic strategy for breast cancer treatment. Additionally, using copper ionophores and copper complexes combined with nanomaterials to induce cuproptosis may provide a potential approach to eliminating drug-resistant breast cancer cells, thus improving the therapeutic efficacy of chemotherapy, radiotherapy, and immunotherapy and eventually eradicating breast tumors. This review aims to highlight the practical significance of cuproptosis-related genes and the induction of cuproptosis in the clinical diagnosis and treatment of breast cancer. We examine the potential of cuproptosis as a novel therapeutic target for breast cancer, and we explore the present challenges and limitations of this approach. Our objective is to provide innovative ideas and references for the development of breast cancer treatment strategies based on cuproptosis.

HSF1 protects cells from cadmium toxicity by governing proteome integrity.

BACKGROUND: Cadmium toxicity has been associated with disruption of protein homeostasis by interfering with protein folding processes. Heat shock factor 1 (HSF1) coordinates the rapid and extensive cellular response to maintain proteomic balance facing the challenges from many environmental stressors. Thus, we suspect that HSF1 may shield cells from cadmium toxicity by conserving proteome integrity. RESULTS: Here, we demonstrate that cadmium, a highly poisonous metal, induces aggregation of cytosolic proteins in human cells, which disrupts protein homeostasis and activates HSF1. Cadmium exposure increases HSF1's phosphorylation, nuclear translocation and DNA bindings. Aside from this, HSF1 goes through liquid-liquid phase separation to form small nuclear condensates upon cadmium exposure. A specific regulatory domain of HSF1 is critical for HSF1's phase separation capability. Most importantly, human cells with impaired HSF1 are sensitized to cadmium, however, cells with overexpressed HSF1 are protected from cadmium toxicity. Overexpression of HSF1 in human cells reduces protein aggregates, amyloid fibrils and DNA damages to antagonize cadmium toxicity. CONCLUSIONS: HSF1 protects cells from cadmium toxicity by governing the integrity of both proteome and genome. Similar mechanisms may enable HSF1 to alleviate cellular toxicity caused by other heavy metals. HSF1's role in cadmium exposure may provide important insights into the toxic effects of heavy metals on human cells and body organs, allowing us to better manage heavy metal poisoning.

The tumour-promoting role of protein homeostasis: Implications for cancer immunotherapy.

Protein homeostasis, an important aspect of cellular fitness that encompasses the balance of production, folding and degradation of proteins, has been linked to several diseases of the human body. Multiple interconnected pathways coordinate to maintain protein homeostasis within the cell. Recently, the role of the protein homeostasis network in tumorigenesis and tumour progression has gradually come to light. Here, we summarize the involvement of the most prominent components of the protein quality control mechanisms (HSR, UPS, autophagy, UPR and ERAD) in tumour development and cancer immunity. In addition, evidence for protein quality control mechanisms and targeted drugs is outlined, and attempts to combine these drugs with cancer immunotherapy are discussed. Altogether, combination therapy represents a promising direction for future investigations, and this exciting insight will be further illuminated by the development of drugs that can reach a balance between the benefits and hazards associated with protein homeostasis interference.

Heat shock factor 1 (HSF1) specifically potentiates c-MYC-mediated transcription independently of the canonical heat shock response.

Despite its pivotal roles in biology, how the transcriptional activity of c-MYC is tuned quantitatively remains poorly defined. Here, we show that heat shock factor 1 (HSF1), the master transcriptional regulator of the heat shock response, acts as a prime modifier of the c-MYC-mediated transcription. HSF1 deficiency diminishes c-MYC DNA binding and dampens its transcriptional activity genome wide. Mechanistically, c-MYC, MAX, and HSF1 assemble into a transcription factor complex on genomic DNAs, and surprisingly, the DNA binding of HSF1 is dispensable. Instead, HSF1 physically recruits the histone acetyltransferase general control nonderepressible 5 (GCN5), promoting histone acetylation and augmenting c-MYC transcriptional activity. Thus, we find that HSF1 specifically potentiates the c-MYC-mediated transcription, discrete from its canonical role in countering proteotoxic stress. Importantly, this mechanism of action engenders two distinct c-MYC activation states, primary and advanced, which may be important to accommodate diverse physiological and pathological conditions.

Self-assembled biobased chitosan hybrid carrying N/P/B elements for polylactide with enhanced fire safety and mechanical properties.

The inherent shortcomings such as flammability, brittleness, and low crystallinity limit the broad applications of poly(lactic acid) (PLA). To improve the fire resistance and mechanical properties of PLA, a chitosan-based core-shell flame retardant additive (APBA@PA@CS) was prepared for PLA via the self-assembly of interionic interactions among chitosan (CS), phytic acid (PA), and 3-aminophenyl boronic acid (APBA). The peak heat release rate (pHRR) and total heat release rate (THR) of PLA composite containing 3 wt% APBA@PA@CS decreased from 460.1 kW/m2 and 75.8 MJ/m2 to 419.0 kW/m2 and 53.1 MJ/m2, respectively. The presence of APBA@PA@CS contributed to the formation of a high-quality char layer rich in phosphorus and boron in the condensed phase and released non-flammable gases in the gas phase to hinder the exchange of heat and O2, thereby having a synergistic flame retardant effect. Meanwhile, the tensile strength, elongation at break, impact strength, and crystallinity of PLA/APBA@PA@CS were increased by 3.7 %, 17.4 %, 5.3 %, and 55.2 %, respectively. This study provides a feasible route to construct a chitosan-based N/B/P tri-element hybrid to improve the fire safety performance and mechanical properties of PLA biocomposites.

Engineered Microparticles for Treatment of Murine Brain Metastasis by Reprograming Tumor Microenvironment and Inhibiting MAPK Pathway.

Brain metastases (BRM) are common in advanced lung cancer. However, their treatment is challenging due to the blood-brain barrier (BBB) and the immunosuppressive tumor microenvironment (ITME). Microparticles (MPs), a type of extracellular vesicle, can serve as biocompatible drug delivery vehicles that can be further modulated with genetic engineering techniques. MPs prepared from cells induced with different insults are compared and it is found that radiation-treated cell-released microparticles (RMPs) achieve optimal targeting and macrophage activation. The enzyme ubiquitin-specific protease 7 (USP7), which simultaneously regulates tumor growth and reprograms M2 macrophages (M2Φ), is found to be expressed in BRM. Engineered RMPs are then constructed that comprise: 1) the RMP carrier that targets and reprograms M2Φ; 2) a genetically expressed SR-B1-targeting peptide for improved BBB permeability; and 3) a USP7 inhibitor to kill tumor cells and reprogram M2Φ. These RMPs successfully cross the BBB and target M2Φ in vitro and in vivo in mice, effectively reprogramming M2Φ and improving survival in a murine BRM model. Therapeutic effects are further augmented when combined with immune checkpoint blockade. This study provides proof-of-concept for the use of genetically engineered MPs for the treatment of BRM.

Artificial Intelligence-Assisted Ultrasound Diagnosis on Infant Developmental Dysplasia of the Hip Under Constrained Computational Resources.

OBJECTIVES: Ultrasound (US) is important for diagnosing infant developmental dysplasia of the hip (DDH). However, the accuracy of the diagnosis depends heavily on expertise. We aimed to develop a novel automatic system (DDHnet) for accurate, fast, and robust diagnosis of DDH. METHODS: An automatic system, DDHnet, was proposed to diagnose DDH by analyzing static ultrasound images. A five-fold cross-validation experiment was conducted using a dataset containing 881 patients to verify the performance of DDHnet. In addition, a blind test was conducted on 209 patients (158 normal and 51 abnormal cases). The feasibility and performance of DDHnet were investigated by embedding it into ultrasound machines at low computational cost. RESULTS: DDHnet obtained reliable measurements and accurate diagnosis predictions. It reported an intra-class correlation coefficient (ICC) on α angle of 0.96 (95% CI: 0.93-0.97), ß angle of 0.97 (95% CI: 0.95-0.98), FHC of 0.98 (95% CI: 0.96-0.99) and PFD of 0.94 (95% CI: 0.90-0.96) in abnormal cases. DDHnet achieved a sensitivity of 90.56%, specificity of 100%, accuracy of 98.64%, positive predictive value (PPV) of 100%, and negative predictive value (NPV) of 98.44% for the diagnosis of DDH. For the measurement task on the US device, DDHnet took only 1.1 seconds to operate and complete, whereas the experienced senior expert required an average 41.4 seconds. CONCLUSIONS: The proposed DDHnet demonstrate state-of-the-art performance for all four indicators of DDH diagnosis. Fast and highly accurate DDH diagnosis is achievable through DDHnet, and is accessible under constrained computational resources.

[Penile cancer with perineural invasion is more prone to postoperative recurrence].

OBJECTIVE: To explore the correlation between perineural invasion and postoperative recurrence in patients surgically treated for penile cancer. METHODS: We conducted a retrospective analysis of the clinical data on 18 penile cancer patients surgically treated in our hospital from January 2018 to December 2021, 8 with postoperative recurrence (the recurrence group) and the other 10 without (the non-recurrence control group). We compared the two groups of patients in the age of onset, tumor-node-metastasis (TNM) stages, American Joint Committee on Cancer (AJCC) prognosis stages, surgical methods, perineural invasion and recurrence time. We analyzed the differences in postoperative recurrence using the Kaplan Meier plotted survival curve and in independent risk factors in predicting postoperative recurrence using the ROC curve. RESULTS: Compared with the non-recurrence controls, the patients in the recurrence group had a significantly older age of onset (P=0.0411) and severer perineural invasion (P<0.001), and those with perineural invasion had a shorter recurrence time (P<0.001), which was an independent risk factor for postoperative recurrence. The areas under the ROC curves for perineural invasion and age were 0.885 and 0.213, respectively. CONCLUSION: Penile cancer with perineural invasion is more prone to and perineural invasion is an independent risk factor for postoperative recurrence of the malignancy.

Ultrasound findings in neonates with alveolar capillary dysplasia with misalignment of the pulmonary veins: report of two cases.

Alveolar capillary dysplasia with misalignment of the pulmonary veins (ACDMPV) is a rare congenital pulmonary disease that affects newborns. Most patients with ACDMPV are born at full term and are healthy. The main clinical manifestations are refractory pulmonary hypertension and pulmonary failure with gastrointestinal, urinary, or cardiac malformations. ACDMPV often progresses rapidly, but no conventional biological or imaging tests other than genetic testing are available for its diagnosis. Lung biopsy is currently the gold standard for diagnosis. We herein report two cases of ACDMPV confirmed by pathological examination and discuss their ultrasonographic findings.

A Reconfigurable Two-WSe2 -Transistor Synaptic Cell for Reinforcement Learning.

Reward-modulated spike-timing-dependent plasticity (R-STDP) is a brain-inspired reinforcement learning (RL) rule, exhibiting potential for decision-making tasks and artificial general intelligence. However, the hardware implementation of the reward-modulation process in R-STDP usually requires complicated Si complementary metal-oxide-semiconductor (CMOS) circuit design that causes high power consumption and large footprint. Here, a design with two synaptic transistors (2T) connected in a parallel structure is experimentally demonstrated. The 2T unit based on WSe2 ferroelectric transistors exhibits reconfigurable polarity behavior, where one channel can be tuned as n-type and the other as p-type due to nonvolatile ferroelectric polarization. In this way, opposite synaptic weight update behaviors with multilevel (>6 bit) conductance states, ultralow nonlinearity (0.56/-1.23), and large Gmax /Gmin ratio of 30 are realized. By applying positive/negative reward to (anti-)STDP component of 2T cell, R-STDP learning rules are realized for training the spiking neural network and demonstrated to solve the classical cart-pole problem, exhibiting a way for realizing low-power (32 pJ per forward process) and highly area-efficient (100 µm2 ) hardware chip for reinforcement learning.

Complementary Memtransistor-Based Multilayer Neural Networks for Online Supervised Learning Through (Anti-)Spike-Timing-Dependent Plasticity.

We propose a complete hardware-based architecture of multilayer neural networks (MNNs), including electronic synapses, neurons, and periphery circuitry to implement supervised learning (SL) algorithm of extended remote supervised method (ReSuMe). In this system, complementary (a pair of n- and p-type) memtransistors (C-MTs) are used as an electrical synapse. By applying the learning rule of spike-timing-dependent plasticity (STDP) to the memtransistor connecting presynaptic neuron to the output one whereas the contrary anti-STDP rule to the other memtransistor connecting presynaptic neuron to the teacher one, extended ReSuMe with multiple layers is realized without the usage of those complicated supervising modules in previous approaches. In this way, both the C-MT-based chip area and power consumption of the learning circuit for weight updating operation are drastically decreased comparing with the conventional single memtransistor (S-MT)-based designs. Two typical benchmarks, the linearly nonseparable benchmark XOR problem and Mixed National Institute of Standards and Technology database (MNIST) recognition have been successfully tackled using the proposed MNN system while impact of the nonideal factors of realistic devices has been evaluated.

Three-term conjugate gradient method for X-ray luminescence computed tomography.

X-ray luminescence computed tomography (XLCT) has become an emerging hybrid molecular imaging technology with high detection sensitivity and low cost. However, the inverse problem of reconstruction has severe ill-posed consequences. The original regularization algorithm needs to take much time to solve the problem. To reduce the cost of time, a three-term conjugate gradient (TTCG) algorithm is proposed for XLCT. Useful truncation information is added to the descent direction to find the optimal solution quickly in our proposed algorithm. Both numerical simulation experiments and real experiments are carried out to verify the performance of the algorithm. Experimental results show that the presented algorithm can effectively speed up the reconstruction process.

HSF1 physically neutralizes amyloid oligomers to empower overgrowth and bestow neuroprotection.

The role of proteomic instability in cancer, particularly amyloidogenesis, remains obscure. Heat shock factor 1 (HSF1) transcriptionally governs the proteotoxic stress response to suppress proteomic instability and enhance survival. Paradoxically, HSF1 promotes oncogenesis. Here, we report that AKT activates HSF1 via Ser230 phosphorylation. In vivo, HSF1 enables megalencephaly and hepatomegaly, which are driven by hyperactive phosphatidylinositol 3-kinase/AKT signaling. Hsf1 deficiency exacerbates amyloidogenesis and elicits apoptosis, thereby countering tissue overgrowth. Unexpectedly, HSF1 physically neutralizes soluble amyloid oligomers (AOs). Beyond impeding amyloidogenesis, HSF1 shields HSP60 from direct assault by AOs, averting HSP60 destabilization, collapse of the mitochondrial proteome, and, ultimately, mitophagy and apoptosis. The very same mechanism occurs in Alzheimer's disease. These findings suggest that amyloidogenesis may be a checkpoint mechanism that constrains uncontrolled growth and safeguards tissue homeostasis, congruent with its emerging tumor-suppressive function. HSF1, by acting as an anti-amyloid factor, promotes overgrowth syndromes and cancer but may suppress neurodegenerative disorders.

Searching therapeutic strategy of new coronavirus pneumonia from angiotensin-converting enzyme 2: the target of COVID-19 and SARS-CoV.

Since December 2019, the infection of the new coronavirus (COVID-19) caused an outbreak of new coronavirus pneumonia in Wuhan, China, and caused great public concern. Both COVID-19 and SARS-CoV belong to the coronavirus family and both invade target cells through ACE2. An in-depth understanding of ACE2 and a series of physiological and physiological changes caused by the virus invading the human body may help to discover and explain the corresponding clinical phenomena and then deal with them timely. In addition, ACE2 is a potential therapeutic target. This article will summarize the role of ACE2 in multiple organ damage caused by COVID-19 and SARS-CoV, targeted blocking drugs against ACE2, and drugs that inhibit inflammation in order to provide the basis for subsequent related research, diagnosis and treatment, and drug development.