Explainable Deep Learning and Biomechanical Modeling for TMJ Disorder Morphological Risk Factors.

Clarifying multifactorial musculoskeletal disorder etiologies supports risk analysis and development of targeted prevention and treatment modalities. Deep learning enables comprehensive risk factor identification through systematic analysis of disease datasets but does not provide sufficient context for mechanistic understanding, limiting clinical applicability for etiological investigations. Conversely, multiscale biomechanical modeling can evaluate mechanistic etiology within the relevant biomechanical and physiological context. We propose a hybrid approach combining 3D explainable deep learning and multiscale biomechanical modeling; we applied this approach to investigate temporomandibular joint (TMJ) disorder etiology by systematically identifying risk factors and elucidating mechanistic relationships between risk factors and TMJ biomechanics and mechanobiology. Our 3D convolutional neural network recognized TMJ disorder patients through subject-specific morphological features in condylar, ramus, and chin. Driven by deep learning model outputs, biomechanical modeling revealed that small mandibular size and flat condylar shape were associated with increased TMJ disorder risk through increased joint force, decreased tissue nutrient availability and cell ATP production, and increased TMJ disc strain energy density. Combining explainable deep learning and multiscale biomechanical modeling addresses the "mechanism unknown" limitation undermining translational confidence in clinical applications of deep learning and increases methodological accessibility for smaller clinical datasets by providing the crucial biomechanical context.

Radioactive Hydroxyapatite Microspheres Empower Sustainable In Situ Tumor Vaccination.

Tumor in situ vaccination (ISV) strategies have emerged in clinical trials as promising approaches, involving the release of tumor antigens through local radiotherapy and intratumorally adjuvant injections. However, the current fabrication strategy for achieving a sustainable immune response to ISV remains a pressing challenge. In this study, we present an empowered sustainable ISV method for antitumor therapy using 177Lu-labeled manganese-doped mesoporous hydroxyapatite (177Lu/Mn-HAP) microspheres. The ISV enables the sustained utilization of tumor antigens, leading to the activation of dendritic cells and polarization of macrophages toward the M1 subtype. Consequently, it facilitates the generation of potent CD8+ T-cell responses, enhancing the antitumor effects of internal radiation in both primary and distant tumors. Importantly, this approach achieves complete remission in all tumor-bearing mice and stimulates immune memory to prevent tumor recurrence. Our study highlights a universal and safe ISV strategy capable of inducing potent tumor-specific and sustainable immune response.

Comprehensive analysis of spatial heterogeneity reveals the important role of the upper-layer fermented grains in the fermentation and flavor formation of Qingxiangxing baijiu.

Different spatial positions lead to inconsistent fermentation effects and flavors, however, the spatial heterogeneity of Qingxiangxing (QXX) Baijiu remains unknown. We investigated the microbes, flavors, and physicochemical properties of different layers in fermented grains of QXX Baijiu using Illumina HiSeq sequencing, two-dimensional gas chromatography-mass spectrometry (GC × GC-MS) and ultra-high performance liquid chromatography-mass (UHPLC-MS). A total of 79 volatiles, 1596 metabolites, 50 bacterial genera, and 52 fungal genera were identified. The contents distribution followed the order: upper layer > bottom layer > middle layer. Organic acids and derivatives were the main differential metabolites across the three layers. Starch, pH, and reducing sugar levels increased from the upper to bottom layer. Saccharomyces and Lactobacillus were dominant microbes. Pediococcus, the biomarker of upper layer, showed positive correlations with formic acid, ethyl lactate, acetic acid, ethyl linoleate, and ethyl oleate. These findings deepen our understanding of the fermentation and flavor formation mechanisms of QXX Baijiu.

Comprehensive Collection of Whole-Slide Images and Genomic Profiles for Patients with Bladder Cancer.

Bladder cancer is one of the leading causes of cancer-related mortality in the urinary system. Understanding genomic information is important in the treatment and prognosis of bladder cancer, but the current method used to identify mutations is time-consuming and labor-intensive. There are now many novel and convenient ways to predict cancerous genomics from pathological slides. However, the publicly available datasets are limited, especially for Asian populations. In this study, we developed a dataset consisting of 75 Asian cases of bladder cancers and 112 Whole-Slide Images with one to two images obtained for each patient. This dataset provides information on the most frequently and clinically significant mutated genes derived by whole-exome sequencing in these patients. This dataset will facilitate exploration and development of novel diagnostic and therapeutic technologies for bladder cancer.

Transcriptome analysis shows that Glomus versiforme decrease the accumulation and toxicity of cadmium in Ipomoea aquatic Forsk.

So far, the physiological and molecular mechanisms of the impact of arbuscular mycorrhizal fungus (AMF) on Cd absorption, transport and detoxification in Ipomoea aquatica (water spinach) are still unclear. In the present study, a pot experiment was performed to investigate the impact of AMF-Glomus versiforme (Gv) on the photosynthetic characteristics, Cd uptake, antioxidative system and transcriptome in water spinach in the soils supplemented with 5 mg Cd kg-1. Gv inoculation improved significantly the photosynthetic characteristics and growth of water spinach. Furthermore, Gv colonization significantly promoted the activities of catalase (CAT), peroxidase (POD) and glutathione reductase (GR), contents of glutathione (GSH) and ascorbic acid (AsA), and the total antioxidant capacity (TCA), but decreased malondialdehyde (MDA) content in water spinach. In addition, Gv inoculation significantly increased pH in rhizosphere soils and decreased the Cd concentrations and uptakes in water spinach. Importantly, 2670 differentially expressed genes (DEGs) were screened in water spinach root colonized with Gv in 5 mg Cd kg-1 soil, of which 2008 DEGs were upregulated and 662 DEGs were downregulated. Especially, the expression levels of POD, CAT, GR, dehydroascorbate reductase 2 (DHAR2), glutathione S-transferase U8 (GSTU8) and glutathione synthetase (GSHS) and cytochrome P450 (Cyt P450) genes were significantly up-regulated in water spinach inoculated with Gv. Meanwhile, the plant cadmium resistance protein 2 (PCR2), metal tolerance protein 4 (MTP4), ATP-binding cassette transporter C family member (ABCC), ABC-yeast cadmium factor 1 (ABC-YCF1) and metallothionein (MT) genes were also up-regulated in mycorrhizal water spinach. Our results firstly elucidated the mechanism by which AMF reduced the uptake and phytotoxicity of Cd in water spinach through a transcriptome analysis.

Formate and CO2 Enable Reductive Carboxylation of Imines: Synthesis of Unnatural α-Amino Acids.

Herein, a photocatalytic umpolung strategy for reductive carboxylation of imines for the synthesis of α-amino acids was disclosed. Carbon dioxide radical anion (CO2•-) generated from formate is the key single electron reductant in the reactions. An unprecedentedly broad substrate scope of imines with excellent reaction yields was obtained with carbon dioxide (CO2) and formate salt as carbon sources.

Inoculation of Zaopei with biofortification: Inducing variation in community structure and improving flavor compounds in Nongxiangxing baijiu.

The deterioration of the quality of raw liquor caused by the low content of ethyl hexanoate in Nongxiangxing baijiu has become a pervasive problem in the baijiu industry. Therefore, this study attempted to increase the synthesis of ethyl hexanoate by microorganisms with high esterase activity to increase Zaopei fermentation. The results showed that biofortification was a feasible and important way to improve the quality of the raw liquor and increase the ethyl hexanoate content. Adding Bacillus subtilis, Staphylococcus epidermidis, and Millerozyma farinosa for biofortified fermentation disturbed the microbial community structure of Zaopei and increased the abundance of Wickerhamomyces, Saccharomyces, and Thermoascus. The contents of ethyl hexanoate, ethyl valerate, ethyl caprylate, and ethyl heptanoate also increased noticeably in baijiu. The results of E-nose and sensory analysis tested and verified that the baijiu in the fortified group had better flavor characteristics.

[Progress in the application of artificial intelligence-assisted molecular modification of enzymes].

Natural enzymes are often difficult to meet the needs of application and research in terms of activity, enantiomer selectivity or thermal stability. Therefore, it is an important task of enzyme engineering to explore efficient molecular modification technologies to improve the properties of such enzymes. The molecular modification technologies of enzymes mainly include rational design, directed evolution, and artificial intelligence-assisted design. Directed evolution and rational design are experiment-driven molecular modification approaches of enzymes and have been successfully applied to enzyme engineering. However, due to the huge space sizes of protein sequences and the lack of experimental data, the current modification methods still face major challenges. With the development of next-generation sequencing, high-throughput screening, protein databases, and artificial intelligence (AI), data-driven enzyme engineering is emerging as a promising solution to these challenges. The AI-assisted statistical learning method has been used to establish a model for predicting the sequence/structure-properties of enzymes in a data-driven manner. Excellent mutant enzymes can be selected according to the prediction results, which greatly improve the efficiency of molecular modification. Considering the application requirements of molecular modification of enzymes, this paper reviews the data acquisition methods and application examples of AI-assisted molecular modification of enzymes, with focuses on the convolutional neural network method for predicting protein thermostability, aiming to provide reference for researchers in this field.

Analysis of risk factors associated with pre-myopia among primary school students in the Mianyang Science City.

Objectives To find out the prevalence rate of pre-myopia among primary school students in the Mianyang Science City Area, analyze its related risk factors, and thus provide a reference for local authorities to formulate policies on the prevention and control of myopia for primary school students. Methods From September to October 2021, Cluster sampling was adopted by our research group to obtain the vision levels of primary school students employing a diopter test in the Science City Area. In addition, questionnaires were distributed to help us find the risk factors associated with pre-myopia. Through the statistical analysis, we identify the main risk factors for pre-myopia and propose appropriate interventions. Results The prevalence rate of pre-myopia among primary school students in the Science City Area was 45.27% (1020/2253), of which 43.82% were boys and 46.92% were girls, with no statistically significant difference in the prevalence rate of myopia between boys and girls (2 =2.171, P=0.141). The results of the linear trend test showed that the prevalence rate of pre-myopia tends to decrease with increasing age (Z=296.521, P=0.000). Logistic regression analysis demonstrated that the main risk factors for pre-myopia were having at least one parent with myopia, spending less than 2 hours a day outdoors, using the eyes continuously for more than 1 hour, looking at electronic screens for more than 2 hours, and having an improper reading and writing posture. Conclusion The Science City Area has a high prevalence rate of pre-myopia among primary school students. It is proposed that students, schools, families, and local authorities work together to increase the time spent outdoors, reduce digital screens and develop scientific use of eye habits.

The Application of Intraoperative Ultrasound with Burr Hole Probe in Minimally Invasive Diagnosis and Treatment in Neurosurgery.

OBJECTIVE: To summarize the preliminary application experience of intraoperative ultrasound with burr hole probe in minimally invasive neurosurgery and to explore its application value. METHODS: Thirty-one patients who underwent intraoperative ultrasound guided puncture with burr hole probe in our center from August 2018 to May 2024 were collected, including 16 cases of ventriculoperitoneal shunt operation, 6 cases of assisted stereotactic needle biopsy, 3 cases of intracranial pressure probe implantation in lateral ventricle, 3 cases of brain abscess puncture for external drainage, and 3 cases of intracranial cyst puncture and peritoneal drainage. During the procedures, the burr hole probe was used to locate the intracranial targets and guide the puncture. The postoperative computed tomography (CT) scans or combined postoperative pathological results could verify the accuracy of puncture. In addition, the intervention effect and recovery status of patients were also recorded. RESULTS: The intraoperative ultrasound with burr hole probe could clearly display all the purposed targets and accurately guide the puncture procedures in all cases. All patients achieved satisfactory diagnostic and therapeutic results without new neurological dysfunction and serious complications. CONCLUSIONS: The intraoperative ultrasound with burr hole probe is an effective device for demonstrating intracranial structures. It not only enables minimally invasive and precise diagnosis or treatment of many neurosurgical diseases, but also is simple and safe to operate, which has important promotional value in the neurosurgery.

Raman spectroscopy for esophageal tumor diagnosis and delineation using machine learning and the portable Raman spectrometer.

Esophageal cancer is one of the leading causes of cancer-related deaths worldwide. The identification of residual tumor tissues in the surgical margin of esophageal cancer is essential for the treatment and prognosis of cancer patients. But the current diagnostic methods, either pathological frozen section or paraffin section examination, are laborious, time-consuming, and inconvenient. Raman spectroscopy is a label-free and non-invasive analytical technique that provides molecular information with high specificity. Here, we report the use of a portable Raman system and machine learning algorithms to achieve accurate diagnosis of esophageal tumor tissue in surgically resected specimens. We tested five machine learning-based classification methods, including k-Nearest Neighbors, Adaptive Boosting, Random Forest, Principal Component Analysis-Linear Discriminant Analysis, and Support Vector Machine (SVM). Among them, SVM shows the highest accuracy (88.61 %) in classifying the esophageal tumor and normal tissues. The portable Raman system demonstrates robust measurements with an acceptable focal plane shift of up to 3 mm, which enables large-area Raman mapping on resected tissues. Based on this, we finally achieve successful Raman visualization of tumor boundaries on surgical margin specimens, and the Raman measurement time is less than 5 min. This work provides a robust, convenient, accurate, and cost-effective tool for the diagnosis of esophageal cancer tumors, advancing toward Raman-based clinical intraoperative applications.

A viral small interfering RNA-host plant mRNA pathway modulates virus-induced drought tolerance by enhancing autophagy.

Virus-induced drought tolerance presents a fascinating facet of biotic-abiotic interaction in plants, yet its molecular intricacies remain unclear. Our study shows that cowpea mild mottle virus (CPMMV) infection enhances drought tolerance in common bean (Phaseolus vulgaris) plants through a virus-derived small interfering RNA (vsiRNA)-activated autophagy pathway. Specifically, a 21-bp vsiRNA originating from the CPMMV Triple Gene Block1 (TGB1) gene targeted the 5' untranslated region (UTR) of the host Teosinte branched 1, Cycloidea, Proliferating Cell Factor (TCP) transcription factor gene PvTCP2, independent of the known role of TGB1 as an RNA silencing suppressor. This targeting attenuated the expression of PvTCP2, which encodes a transcriptional repressor, and in turn upregulated the core autophagy-related gene (ATG) PvATG8c, leading to activated autophagy activity surpassing the level induced by drought or CPMMV infection alone. The downstream EARLY RESPONSIVE TO DEHYDRATION (ERD) effector PvERD15 is a homologue of Arabidopsis thaliana AtERD15, which positively regulates stomatal aperture. PvERD15 was degraded in PvATG8c-mediated autophagy. Therefore, we establish a TGB1-PvTCP2-PvATG8c-PvERD15 module as a trans-kingdom fine-tuning mechanism that contributes to virus-induced drought tolerance in plant-drought-virus interactions.

Methods for Functional Physiological Phenotyping and High-Order Data Quantification.

This chapter presents the application of Plantarray, a high-throughput platform commercially available for noninvasive monitoring of plant functional physiology phenotyping (FPP). The platform continuously measures water flux in the soil-plant-atmosphere for each plant in dynamic environments. To better interpret the massive phenotypic data acquired with FPP, several quantitative analysis methods were demonstrated for various types of data. Simple mathematical models were utilized to fit characteristic parameters of plant transpiration response to drought stress. Additionally, ecophysiological models were employed to quantify the sensitivity of transpiration to radiation and vapor pressure deficit (VPD) as component traits and predict more complex higher-order traits. The established protocols provide a tangible tool for integrating FPP and model analysis to address complex traits.

Constipation anti-aging effects by dairy-based lactic acid bacteria.

Constipation, which refers to difficulties in defecation and infrequent bowel movement in emptying the gastrointestinal system that ultimately produces hardened fecal matters, is a health concern in livestock and aging animals. The present study aimed to evaluate the potential effects of dairy-isolated lactic acid bacteria (LAB) strains to alleviate constipation as an alternative therapeutic intervention for constipation treatment in the aging model. Rats were aged via daily subcutaneous injection of D-galactose (600 mg/body weight [kg]), prior to induction of constipation via oral administration of loperamide hydrochloride (5 mg/body weight [kg]). LAB strains (L. fermentum USM 4189 or L. plantarum USM 4187) were administered daily via oral gavage (1 × 10 Log CFU/day) while the control group received sterile saline. Aged rats as shown with shorter telomere lengths exhibited increased fecal bulk and soften fecal upon administration of LAB strains amid constipation as observed using the Bristol Stool Chart, accompanied by a higher fecal moisture content as compared to the control (p < 0.05). Fecal water-soluble metabolite profiles showed a reduced concentration of threonine upon administration of LAB strains compared to the control (p < 0.05). Histopathological analysis also showed that the administration of LAB strains contributed to a higher colonic goblet cell count as compared to the control (p < 0.05). The present study illustrates the potential of dairy-sourced LAB strains as probiotics to ameliorate the adverse effect of constipation amid aging, and as a potential dietary intervention strategy for dairy foods including yogurt and cheese.

Comparison of the effects of gasoline burn and chromic acid burn on different internal organs and immune functions in rats.

Burn as physical injury ranks as the fourth most prevalent trauma across the world. In this study, we aimed to compare the impact of gasoline burn and chromic acid burn on the internal organs and immune functions in rats. The results showed that the levels of methemoglobin (MHb) to total hemoglobin (Hb) as well as the Cr6+ content showed significant elevation in the chromic acid burn group relative to the gasoline burn group. HE staining was used to evaluate the histological changes in the injured tissues as well as the tissues excised from internal organs. We found that chromic acid burn-induced more severe damage to rat tissues. Gasoline burn showed no significant impact on the intestinal tissues of rats, while the chromic acid burn-induced increased cell death in rat intestines. Moreover, the results of HE staining also revealed that gasoline burn and chromic acid burn showed no evident impact on rat hearts. Gasoline burn also showed no significant effects on the liver, lungs and kidneys of rats, while the chromic acid burn caused injuries to such internal organs in comparison with the control and gasoline burn groups. In addition, the MPO activity was higher in the liver, intestine, lungs and kidneys of rats with chromic acid burn. Furthermore, the expression of inflammation response cytokines was examined in the serum of rats. The results demonstrated that the levels of IL-6, IL-1ß and TNF-α showed a significant increase in both the gasoline burn and chromic acid burn groups of rats relative to the control, and the levels were higher in the chromic acid burn group in comparison with the gasoline burn group. In conclusion, the chromic acid burn-induced more severe organ injury, inflammation and immune response compared with the gasoline burn, which may provide reference data for the clinical treatment of patients with different burn injuries.

Non-targeted analysis and toxicity prediction for evaluation of photocatalytic membrane distillation removing organic contaminants from hypersaline oil and gas field-produced water.

Membrane distillation (MD) has received ample recognition for treating complex wastewater, including hypersaline oil and gas (O&G) produced water (PW). Rigorous water quality assessment is critical in evaluating PW treatment because PW consists of numerous contaminants beyond the targets listed in general discharge and reuse standards. This study evaluated a novel photocatalytic membrane distillation (PMD) process, with and without a UV light source, against a standard vacuum membrane distillation (VMD) process for treating PW, utilizing targeted analyses and a non-targeted chemical identification workflow coupled with toxicity predictions. PMD with UV light resulted in better removals of dissolved organic carbon, ammoniacal nitrogen, and conductivity. Targeted organic analyses identified only trace amounts of acetone and 2-butanone in distillates. According to non-targeted analysis, the number of suspects reduced from 65 in feed to 25-30 across all distillate samples. Certain physicochemical properties of compounds influenced contaminant rejection in different MD configurations. According to preliminary toxicity predictions, VMD, PMD with and without UV distillate samples, respectively contained 21, 22, and 23 suspects associated with critical toxicity concerns. Overall, non-targeted analysis together with toxicity prediction provides a competent supportive tool to assess treatment efficiency and potential impacts on public health and the environment during PW reuse.

Ultrasensitive SERS quantitative detection of antioxidants via diazo derivatization reaction and deep learning for signal fluctuation mitigation.

Synthetic antioxidants serve as essential protectors against oxidation and deterioration of edible oils, however, prudent evaluation is necessary regarding potential health risks associated with excessive intake. The direct adsorption of antioxidants onto conventional surface-enhanced Raman scattering (SERS) substrates is challenging due to the presence of phenolic hydroxyl groups in their molecular structures, resulting in weak Raman scattering signals and rendering direct SERS detection difficult. In this study, a diazo derivatization reaction was employed to enhance SERS signals by converting antioxidant molecules into azo derivatives, enabling the amplification of the weak Raman scattering signals through the strong vibrational modes induced by the N = N double bond. The resulting diazo derivatives were characterized using UV-visible absorption and infrared spectroscopy, confirming the occurrence of diazo derivatization of the antioxidants. The proposed method successfully achieved the rapid detection of three commonly used synthetic antioxidants, namely butylated hydroxyanisole (BHA), tert-butylhydroquinone (TBHQ), and propyl gallate (PG) on interfacial self-assembled gold nanoparticles. Furthermore, rapid predictions of BHA, PG, and TBHQ within the concentration range of 1 × 10-6 to 2 × 10-3 mol/L were achieved by integrating a convolutional neural network model. The predictive range of this model surpassed the traditional quantitative method of manually selecting characteristic peaks, with linear coefficients (R2) of 0.9992, 0.9997, and 0.9997, respectively. The recovery of antioxidants in real soybean oil samples ranged from 73.0 % to 126.4 %. Based on diazo derivatization, the proposed SERS method eliminates the need for complex substrates and enables the analysis and determination of synthetic antioxidants in edible oils within 20 min, providing a convenient analytical approach for quality control in the food industry.