Precision HER2: a comprehensive AI system for accurate and consistent evaluation of HER2 expression in invasive breast Cancer.

BACKGROUND: With the development of novel anti-HER2 targeted drugs, such as ADCs, it has become increasingly important to accurately interpret HER2 expression in breast cancer. Previous studies have demonstrated high intra-observer and inter-observer variabilities in evaluating HER2 staining by human eyes. There exists a strong requirement to develop artificial intelligence (AI) systems to achieve high-precision HER2 expression scoring for better clinical therapy. METHODS: In the present study, we collected breast cancer tissue samples and stained consecutive sections with anti-Calponin and anti-HER2 antibodies. High-quality digital images were selected from immunohistochemical slides and interpreted as HER2 3+, 2+, 1+, and 0. AI models were trained and assessed using annotated training and testing sets. The AI model was trained to automatically identify ductal carcinoma in situ (DCIS) by Calponin staining and myoepithelial annotation and filter out DCIS components in HER2-stained slides using image-overlapping techniques. Furthermore, we organized two-phase validation studies. In phase one, pathologists interpreted 112 HER2 whole-slide images (WSIs) without AI assistance, whereas in phase two, pathologists read the same slides using the AI system after a washing period of 2 weeks. RESULTS: Our AI model greatly improved the accuracy of reading (0.902 vs. 0.710). The number of HER2 1 + patients misdiagnosed as HER2 0 was significantly reduced (32/279 vs. 65/279), and they benefitted from ADC drugs. In addition, the AI algorithm improved the intra-group consistency of HER2 readings by pathologists with different years of experience (intra-class correlation coefficient [ICC]: 0.872-0.926 vs. 0.818-0.908), with the improvement most pronounced among junior pathologists (0.885 vs. 0.818). CONCLUSIONS: We proposed a high-precision AI system to identify and filter out DCIS components and automatically evaluate HER2 expression in invasive breast cancer.

Alantolactone improves cognitive impairment in rats with Porphyromonas gingivalis infection by inhibiting neuroinflammation, oxidative stress, and reducing Aß levels.

Neuroinflammation caused by the chronic periodontal pathogen Porphyromonas gingivalis is growing regarded as as a key factor in the pathogenesis of Alzheimer's disease (AD). Alantolactone (AL), a sesquiterpene lactone isolated from the root of Inula racemosa Hook. f, has been proven to provide various neuroprotective effects. However, whether AL can improve cognitive impairment caused by P. gingivalis infection remains unclear. In this research, a rat model of P. gingivalis infection was used to examine the neuroprotective benefits of AL. The results revealed that 6 weeks of AL treatment (50 and 100 mg/kg) shortened escape latency and increased the number of crossings over the platform location and time spent in the target quadrant of P. gingivalis-infected rats in the Morris water maze experiment. By activating the Nrf2/HO-1 pathway, AL suppressed malondialdehyde (MDA) levels and simultaneously increased the activity of total superoxide dismutase (T-SOD). Furthermore, AL lowered the presence of IL-6, IL-1ß, and TNFα in the hippocampal and cortical tissues of P. gingivalis-infected rats by inhibiting astrocyte and microglial activation and NF-κB phosphorylation. AL also significantly reduced Aß levels in the cortical and hippocampus tissues of rats infected with P. gingivalis. In conclusion, AL improved cognitive impairment in P. gingivalis-infected rats by inhibiting neuroinflammation, reducing Aß1-42 level, and exerting antioxidative stress effects.

Improving Active Site Local Proton Transfer in Porous Organic Polymers for Boosted Oxygen Electrocatalysis.

Improving proton transfer is vital for electrocatalysis with porous materials. Although several strategies are reported to assist proton transfer in channels, few studies are dedicated to improving proton transfer at the local environments of active sites in porous materials. Herein, we report on new Co-corrole-based porous organic polymers (POPs) with improved proton transfer for electrocatalytic oxygen reduction reaction (ORR) and oxygen evolution reaction (OER). By tuning the pore sizes and installing proton relays at Co corrole sites, we designed and synthesized POP-2-OH with improved proton transfer both in channels and at local Co active sites. This POP shows remarkable activity for both electrocatalytic ORR with E1/2 = 0.91 V vs RHE and OER with h10 = 255 mV. Therefore, this work is significant to present a strategy to improve active site local proton transfer in porous materials and highlight the key role of such structural functionalization in boosting oxygen electrocatalysis.

Adaptive control for circulating cooling water system using deep reinforcement learning.

Due to the complex internal working process of circulating cooling water systems, most traditional control methods struggle to achieve stable and precise control. Therefore, this paper presents a novel adaptive control structure for the Twin Delayed Deep Deterministic Policy Gradient algorithm, which is based on a reference trajectory model (TD3-RTM). The structure is based on the Markov decision process of the recirculating cooling water system. Initially, the TD3 algorithm is employed to construct a deep reinforcement learning agent. Subsequently, a state space is selected, and a dense reward function is designed, considering the multivariable characteristics of the recirculating cooling water system. The agent updates its network based on different reward values obtained through interactions with the system, thereby gradually aligning the action values with the optimal policy. The TD3-RTM method introduces a reference trajectory model to accelerate the convergence speed of the agent and reduce oscillations and instability in the control system. Subsequently, simulation experiments were conducted in MATLAB/Simulink. The results show that compared to PID, fuzzy PID, DDPG and TD3, the TD3-RTM method improved the transient time in the flow loop by 6.09s, 5.29s, 0.57s, and 0.77s, respectively, and the Integral of Absolute Error(IAE) indexes decreased by 710.54, 335.1, 135.97, and 89.96, respectively, and the transient time in the temperature loop improved by 25.84s, 13.65s, 15.05s, and 0.81s, and the IAE metrics were reduced by 143.9, 59.13, 31.79, and 1.77, respectively. In addition, the overshooting of the TD3-RTM method in the flow loop was reduced by 17.64, 7.79, and 1.29 per cent, respectively, in comparison with the PID, the fuzzy PID, and the TD3.

Nonadiabatic molecular dynamics with subsystem density functional theory: application to crystalline pentacene.

In this work, we report the development and assessment of the nonadiabatic molecular dynamics approach with the electronic structure calculations based on the linearly scaling subsystem density functional method. The approach is implemented in an open-source embedded Quantum Espresso/Libra software specially designed for nonadiabatic dynamics simulations in extended systems. As proof of the applicability of this method to large condensed-matter systems, we examine the dynamics of nonradiative relaxation of excess excitation energy in pentacene crystals with the simulation supercells containing more than 600 atoms. We find that increased structural disorder observed in larger supercell models induces larger nonadiabatic couplings of electronic states and accelerates the relaxation dynamics of excited states. We conduct a comparative analysis of several quantum-classical trajectory surface hopping schemes, including two new methods proposed in this work (revised decoherence-induced surface hopping and instantaneous decoherence at frustrated hops). Most of the tested schemes suggest fast energy relaxation occurring with the timescales in the 0.7-2.0 ps range, but they significantly overestimate the ground state recovery rates. Only the modified simplified decay of mixing approach yields a notably slower relaxation timescales of 8-14 ps, with a significantly inhibited ground state recovery.

Relationship between paravertebral muscle degeneration and spinal-pelvic sagittal parameters in patients with lumbar disc herniation.

Lumbar disc herniation (LDH) is a clinically common degenerative disease of the spine, and spinal-pelvic sagittal balance and paravertebral muscle degeneration have been a research focus in recent years. To explore the relationship between the degeneration of paravertebral muscle and the changes in the spinal-pelvic sagittal parameters in LDH patients, 105 LDH patients (experimental group) and 63 healthy volunteers (control group) hospitalized in Ordos Central Hospital from January 2020 and January 2023 were included as study subjects. All the patients underwent lumbar magnetic resonance imaging and spinal X-ray using uniform criteria. The correlation between the paravertebral muscle and sagittal-pelvic sagittal parameters of the patients with LDH was obtained from two imaging examinations, and the data were organized and grouped to explore the correlation between these parameters. No significant difference in general data existed between the groups (P > 0.05). In the L4/5 LDH patients group, the ratio of fat infiltration (FIR) in the healthy side [multifidus (MF) and erector spinae (ES)] was negatively correlated with the lumbar lordosis (LL) (r = -0.461, r = -0.486, P < 0.05). The relative cross-sectional area (RCSA) of the bilateral MF was positively correlated with the pelvic tilt (r = 0.549, r = 0.515, P < 0.05). The bilateral ES RCSA was negatively correlated with the sagittal vertical axis (r = -0.579, r = -0.621, P < 0.05). A positive correlation existed between the RCSA and thoracic kyphosis in the healthy side ES (r = 0.614, P < 0.05). In the L5/S1 LDH patients group, a negative correlation existed between the FIR and LL in the healthy side ES (r = -0.579, P < 0.05). Thus, the paravertebral muscle parameters were correlated with the spinal-pelvic sagittal parameters in the patients with LDH.

Corrigendum: The effect of temperature on dengue virus transmission by Aedes mosquitoes.

[This corrects the article DOI: 10.3389/fcimb.2023.1242173.].

Multivariable Coupled System Control Method Based on Deep Reinforcement Learning.

Due to the multi-loop coupling characteristics of multivariable systems, it is difficult for traditional control methods to achieve precise control effects. Therefore, this paper proposes a control method based on deep reinforcement learning to achieve stable and accurate control of multivariable coupling systems. Based on the proximal policy optimization algorithm (PPO), this method selects tanh as the activation function and normalizes the advantage function. At the same time, based on the characteristics of the multivariable coupling system, the reward function and controller are redesigned structures, achieving stable and precise control of the controlled system. In addition, this study used the amplitude of the control quantity output by the controller as an indicator to evaluate the controller's performance. Finally, simulation verification was conducted in MATLAB/Simulink. The experimental results show that compared with decentralized control, decoupled control and traditional PPO control, the method proposed in this article achieves better control effects.

The effect of temperature on dengue virus transmission by Aedes mosquitoes.

Dengue is prevalent in tropical and subtropical regions. As an arbovirus disease, it is mainly transmitted by Aedes aegypti and Aedes albopictus. According to the previous studies, temperature is closely related to the survival of Aedes mosquitoes, the proliferation of dengue virus (DENV) and the vector competence of Aedes to transmit DENV. This review describes the correlations between temperature and dengue epidemics, and explores the potential reasons including the distribution and development of Aedes mosquitoes, the structure of DENV, and the vector competence of Aedes mosquitoes. In addition, the immune and metabolic mechanism are discussed on how temperature affects the vector competence of Aedes mosquitoes to transmit DENV.

Spinal­pelvic sagittal imbalance and paraspinal muscle degeneration in patients with degenerative lumbar spinal stenosis: A monocentric, prospective and observational study.

Degenerative lumbar spinal stenosis (DLSS) is a condition in which the body is held in a poor posture for a long period of time, resulting in a change in the stress structure of the lumbar spine that causes degenerative changes in the muscles of the spine. The sagittal balance of the spine and pelvis and the degeneration of the paravertebral muscles have been the focus of recent research. To explore the relationship between paraspinal muscle degeneration and changes in spine-pelvic sagittal parameters in patients with DLSS, 95 patients with DLSS (experimental group) and 70 healthy volunteers (control group) hospitalized in the Ordos Central Hospital between January 2020 and January 2022 were included as study subjects. All patients underwent lumbar magnetic resonance imaging and spinal X-ray using uniform criteria. The correlation between paravertebral muscle parameters and sagittal-pelvic sagittal parameters in patients with DLSS was obtained from two imaging examinations, and the data were organized and grouped in order to explore the correlation between these parameters. There was no significant difference in the general data between the two groups (P>0.05). In the L4-5 DLSS patient group, the ratio of fat infiltration in the right erector spinae (ES) muscle was negatively correlated with thoracic kyphosis (TK) (r=-0.536; P<0.05) but not significantly in the left side. The relative cross-sectional area of the left multifidus muscle (MF RCSA) was positively correlated with TK (r=0.685; r=0.615; P<0.05) but not significantly in the right side. In the L5-S1DLSS patient group, the right MF RCSA and right ES RCSA were significantly positively correlated with TK (r=0.685; r=0.615; P<0.05) but not significant in the left side. Thus, paravertebral muscle parameters were correlated with spinal-pelvic sagittal parameters in patients with DLSS.

Artificial intelligence in cancer pathology: Challenge to meet increasing demands of precision medicine.

Clinical efforts on precision medicine are driving the need for accurate diagnostic, new prognostic and novel drug predictive assays to inform patient selection and stratification for disease treatment. Accumulating evidence suggests that a combination of cancer pathology and artificial intelligence (AI) can meet this requirement. In the present review, the past, present and emerging integrations of AI into cancer pathology were comprehensively reviewed, which were divided into four main groups to highlight the roles of AI­integrated cancer pathology in precision medicine. Furthermore, the unsolved problems and future challenges in AI­integrated cancer pathology were also discussed. It was found that, although AI­integrated cancer pathology could enable the amalgamation of complex morphological phenotypes with the multi­omics datasets that drove precision medicine, synergies of cancer pathology with other medical tools could be more promising for the clinic when making an accurate and rapid decision in personalized treatments for patients. It was hypothesized by the authors that exploring the potential advantages of the multimodal integration of cancer pathology, imaging­omics, protein­omics and other­omics, as well as clinical data to decide upon appropriate management and improve patient outcomes may be the most challenging issue of cancer precision medicine in the future.

Super-tough polylactic acid (PLA)/poly(butylene succinate) (PBS) materials prepared through reactive blending with epoxy-functionalized PMMA-GMA copolymer.

High-performance biosourced polylactic acid (PLA)/poly(butylene succinate) (PBS) blends with small amounts of compatibilizer, epoxy-functionalized methyl methacrylate-co-glycidyl methacrylate copolymer (PMMA-GMA), were fabricated by melt compounding. The properties of the modified PLA/PMMA-GMA, PBS/PMMA-GMA, and PLS(PLA/PBS)/PMMA-GMA blends were investigated systematically. DSC combined with X-ray diffraction revealed a low-order semi-crystalline structure for all samples. SEM and DMA showed that the compatibility between PLA and PBS was improved after addition of PMMA-GMA. Rheological behavior of blends showed that the addition of PMMA-GMA resulted in a significant improvement in the viscoelasticity. FT-IR spectra confirmed that the interfacial compatibilization between PLA and PBS phases was improved due to the reaction of epoxy groups with terminal groups of PLA and PBS. Finally, the toughness and notched impact strength of the PLA materials were increased significantly. The elongation at break and notched impact strength of PLS/PMMA-GMA was about 55.7 and 6.2 times than neat PLA after incorporation of 7 wt% PMMA-GMA, respectively.

[ZHANG Wei-hua's clinical experience of Zhenjing Anshen method in treatment of insomnia].

The paper summarizes professor ZHANG Wei-hua's clinical experience in treatment of insomnia with Zhenjing Anshen (calming-down the spirit) method. It is believed that insomnia results from the unstable spirit in pathogenesis of TCM. The basic therapeutic principle is regulating the spirit, in which, stabilizing the primary spirit and tranquilizing the heart spirit are emphasized. Main acupoints are Baihui (GV 20), Sishencong (EX-HN 1) and Yintang (GV 24+) to stabilize the primary spirit, located on the head; and Shenmen (HT 7) located on the wrist to calm-down the heart spirit, as well as Sanyinjiao (SP 6) and Yongquan (KI 1) in the lower extremities to benefit yin and balance yang, and then to house the spirit eventually. The needles are inserted in different depths and to various directions. The external application of herbal plaster is combined at Yongquan (KI 1) and the supplementary acupoints are selected in terms of syndrome differentiation. This therapy is simple in acupoint selection and very effective in treatment of insomnia.

[Professor ZHANG Wei-hua's clinical experience in chronic somatic pain treated with zhidong needling techniques].

The paper summarizes professor ZHANG Wei-hua's clinical experience for the treatment of chronic somatic pain with zhidong needling techniques. In terms of the characteristics of chronic somatic pain, professor ZHANG has integrated zhidong needling with acupuncture kinetic therapy. The satisfactory therapeutic effects are obtained by selecting the painful points and regions as the treatment sites and the specific techniques of zhidong needling depending on the size of affected area, the depth of illness, the size and shape of the cord-like muscle, etc. Five techniques of zhidong needling are used accordingly with twirling, pulling, lifting and thrusting, surrounding needling methods involved, as well as with the manipulation speed, direction and frequency considered.

Electrocatalytic Hydrogen Evolution of Bent Bis(dipyrrin) Ni(II) Complexes.

Planar Ni(II) porphyrinoid complexes have been widely used in electrochemical carbon dioxide reduction reaction and oxygen reduction reaction as well as hydrogen evolution reaction (HER). However, nonplanar Ni(II) tetra-pyrrolic complexes have not been thoroughly investigated thus far. In this study, three highly bent bis(dipyrrin) Ni(II) complexes have been synthesized to investigate their structure, electronic property, and electrocatalytic HER activities. Cyclic voltammetry and thin-layer UV-visible spectroelectrochemistry studies revealed four redox processes, yielding two reduced species as the final products. The ic/ip values of phenyl- and pentafluorophenyl-bearing bis(dipyrrin) Ni(II) complexes were >30 when trifluoroacetic acid was used as the proton source, and their Faradaic efficiencies for H2 generation were >93%. Density functional theory calculations of the HERs revealed low endothermic energies of bent bis(dipyrrin) Ni(II) complexes.

DNA tetrahedron-besieged primer and DNAzyme-activated programmatic RCA for low-background electrochemical detection of ochratoxin A.

Ochratoxin A (OTA) is the most toxic class of ochratoxins and has become a major threat to the environment, humans and animals. Therefore, research on the methods for its detection is also more urgent. Herein, we propose a low-background electrochemical biosensor based on a DNA tetrahedron-besieged primer and a DNAzyme-activated programmatic rolling circle amplification (RCA) that can be ultimately utilized for OTA detection in wine samples. Low-background detection can be achieved using the besieged primer via sequenced assembly of DNA tetrahedral nanostructures so that non-specific extensions of primer can be avoided. The target OTA-mediated DNAzyme activation initiates the programmatic RCA. Additionally, the catalytic property of silver nanoclusters (AgNCs) is integrated with the electrochemical assay to achieve high sensitivity for OTA detection. Benefiting from the aforementioned processes, a low-background, and highly sensitive electrochemical biosensor has been successfully constructed. This design is capable of detecting OTA at concentrations from 1 pg/mL to 10 ng/mL, and its lowest concentration limit is 0.773 pg/mL. Simultaneously, its validation in the detection of actual samples reveals that the proposed electrochemical biosensor has a lot of potential in food safety and environmental detection.

An autonomous synthetic DNA machine for ultrasensitive detection of Salmonella typhimurium based on bidirectional primers exchange reaction cascades.

Statistics show that food poisoning caused by Salmonella typhimurium (S. Typhimurium) often tops the list of bacterial food poisoning types in countries around the world. However, detecting traces of S. Typhimurium in real samples remains challenging. In recent years, primer exchange reaction (PER), a new isothermal amplification strategy, has rapidly attracted the attention of researchers in the field of biosensing. In this work, We developed a nanostructure called DNA arch bridge (DAB) and combined the DAB with cascade PER technology to construct a novel bidirectional PER (B-PER) for ultra-sensitive detection of pathogenic bacteria as a novel fluorescent biosensor. This strategy relies on the B-PER reaction mediated by binding of the target and adaptor, which occurs with the assistance of Klenow Fragment (KF) (3'-5'exo) polymerase and produces a good deal of G-quadruplex sequences that generate a fluorescent signal by embedding fluorescent dyes. Under the best conditions, the biosensor achieves ultrasensitive detection of S. Typhimurium, and the detection limit of the strategy is 9.3 cfu mL-1 over the linear detection scope of 101-105 cfu mL-1. The method has the merits of facile operation, rapid response, and high sensitivity. Furthermore, the biosensor is expected to achieve ultrasensitive detection of various small molecules through recognizing different target and primer sequences. Therefore, our proposed strategy provides an efficient, stable, universal, and practical sensing platform for pathogen and other small molecules detection.

Synthesis of Pyridine Heterocyclic Low-Melting-Point Phthalonitrile Monomer and the Effects of Different Curing Agents on Resin Properties.

A phthalonitrile monomer (DPTP) containing pyridine with sulfide bonds was prepared and cured into polymers using different curing agents under the same temperature-programmed process. We characterized and comprehensively evaluated the effects of different curing agents on the thermal and thermomechanical properties of phthalonitrile resin, showing that the DPTP monomer cured with naphthalene-containing curing agent exhibited the best performance among the three polymers. Differential scanning calorimetric (DSC) investigation manifested that the melting point of the DPTP monomer was 61 °C, with a processing window of about 170 °C, suggesting the presence of a wide processing range. Thermogravimetric analysis (TGA) demonstrated the outstanding heat resistance, T5%, of 460 °C in nitrogen, at the same time demonstrating superior long-term stability compared with other commonly used polymer materials, which proves the long-term usage under high temperatures of 300 °C. Dynamic mechanical analysis (DMA) revealed that the storage modulus at 50 °C was 3315 MPa, and the glass transition temperature (Tg) of the polymer was more than 350 °C. Therefore, DPTP resins have favorable thermal stability as well as prominent thermomechanical properties.

Rational Design of Fluorinated Phthalonitrile/Hollow Glass Microsphere Composite with Low Dielectric Constant and Excellent Heat Resistance for Microelectronic Packaging.

High-performance composites with a resin matrix are urgently required for electronic packaging due to their low dielectric constant, outstanding high temperature resistance, excellent corrosion resistance, light weight and easy molding. In this work, hollow-glass-microsphere (HGM)-filled fluorinated-phthalonitrile (PBDP) composites, with filler contents ranging from 0 to 35.0 vol.%, were prepared in order to modify the dielectric properties of the phthalonitrile. Scanning electron microscopy (SEM) observations indicate that the modified HGM particles were uniformly dispersed in the matrix. The PBDP/27.5HGM-NH2 composite demonstrates a low dielectric constant of 1.85 at 12 GHz. The 5% thermogravimetric temperature (T5) of composites with silanized HGM filler (481-486 °C) is higher than the minimum packaging-material requirements (450 °C). In addition, the heat-resistance index (THRI) of PBDP/HGM-NH2 composites reached as high as 268 °C. the storage modulus of PBDP/HGM-NH2 composites were significantly increased to 1283 MPa at 400 °C, an increase by 50%, in comparison to that of PBDP phthalonitrile resin (857 MPa). The excellent dielectric and thermal properties of the present composites may pave a way for comprehensive applications in electronic packaging and thermal management for energy systems.

A Pyridazine-Containing Phthalonitrile Resin for Heat-Resistant and Flame-Retardant Polymer Materials.

In this study, a novel phthalonitrile monomer containing a pyridazine ring, 3,6-bis[3-(3,4-dicyanophenoxy)phenoxy]pyridazine (BCPD) with a low melting point (74 °C) and wide processing window (178 °C), was prepared by a nucleophilic substitution reaction. The molecular structure of the BCPD monomer was identified by Fourier transform infrared spectroscopy (FTIR), and nuclear magnetic resonance spectroscopy (NMR). Poly(BCPD) resins were derived from the formulations by curing at 350 and 370 °C. The thermoset that was post-cured at 370 °C demonstrated outstanding high heat-resistant (glass transition temperature (Tg) > 400 °C, 5% weight loss temperature (T5%) = 501 °C, Yc at 900 °C > 74%) and was flame-retardant (limiting oxygen index (LOI) = 48)). Further, the poly(BCPD) resin simultaneously exhibited a superior storage modulus, which could reach up to 3.8 Gpa at room temperature. Excellent processability and heat resistance were found for phthalonitrile thermosets containing the pyridazine ring, indicating poly(BCPD) resin could be potentially applied as high-temperature structural composite matrices.