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Category: biotech/medical

‘Tour de force’ mouse study shows a gut microbe can promote memory loss

Scientists have plenty of ideas about why aging impairs memory. Reductions in blood flow in the brain, shrinking brain volume, and malfunctioning neural repair systems have all been blamed. Now, new research in mice points to another possible culprit: microbes in the gut.

In a new study, scientists show how a bacterium that is particularly common in older animals can drive memory loss. This microbe makes compounds that impair signaling along neurons connecting the gut with the brain, dampening activity in brain regions associated with learning and memory, the team found.

Research suggests the microbiome may contribute to cognitive decline—but its relevance in humans is unclear.

Ageing promotes metastasis via activation of the integrated stress response

Ageing reprograms the evolutionary trajectory of KRAS-driven lung adenocarcinoma, limiting primary tumour growth while promoting metastatic dissemination through epigenetic activation of the integrated stress response, and a therapeutic opportunity in older patients is revealed.

Cool Qubits Make Faster Decisions

Classical machine learning has benefited several physics subfields, from materials science to medical imaging. Implementing machine-learning algorithms on quantum computers could expand their use to more complex problems and to datasets that are inherently quantum. Nayeli Rodríguez-Briones at the Technical University of Vienna and Daniel Park at Yonsei University in South Korea have now proposed a thermodynamics-inspired protocol that could make quantum machine-learning techniques more efficient [1].

In one common classical machine-learning task, a system is trained on a known dataset and then challenged to classify new data. Its output quantifies both the classification and that classification’s uncertainty. Once the system’s parameters are fixed, evaluating the same data yields the same output. In contrast, the output of a quantum machine-learning algorithm is read out as binary measurements of qubits, which are inherently probabilistic. Because a single measurement provides only limited information, the computation must be repeated many times.

Rodríguez-Briones and Park recognized that how clearly a quantum computer reveals its output is determined by entropy. When the readout qubit is highly polarized—strongly favoring one outcome—its entropy is low. Few repetitions are needed to obtain a firm result. An unpolarized, high-entropy readout qubit returns both states more evenly, meaning more repetitions are required. The researchers showed that the readout qubit’s polarity can be increased by transferring its entropy to ancillary qubits, effectively cooling one while warming the others. Between runs, the ancillary qubits are reset by coupling them to a heat bath. Crucially, this entropy transfer affects the readout qubit’s degree of polarization without changing the encoded decision. The upshot: A given result can be arrived at with fewer repetitions.

Hidden DNA in Plants Reveals a 400 Million Year Evolutionary Secret

Researchers uncovered millions of ancient plant DNA switches—some older than flowering plants themselves—revealing a hidden evolutionary blueprint stretching back 400 million years. Most people have heard the phrase deep space, but scientists also study something known as deep time. Modern geneti

Scientists Solve a Long-Standing Chemistry Challenge With Light-Driven Catalysis

Chemists have developed a light-driven method for producing a rare and highly strained molecular structure known as “housane.” Designing a new drug often starts with a basic but difficult task: making the exact molecular framework needed for a medicine to work. Some important drugs, including pen

Atypical Development of Functional Brain Networks in Neonates with Congenital Heart Disease

New in JNeurosci: fMRI study from Kim et al. reveals that babies with congenital heart disease have altered sensorimotor and limbic brain networks that cardiovascular surgery improves.

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Congenital heart disease (CHD) affects approximately 1% of live births in the United States and is the most prevalent congenital disorder. Despite advances in neonatal cardiovascular surgery improving survival, neurodevelopmental impairments remain prevalent, impacting motor skills, social behavior, and executive function. Motor deficits and long-term challenges in emotional regulation and memory are particularly common. Recent research using resting-state functional MRI (rs-fMRI) has revealed disorganized brain networks in newborns with CHD. However, those few prior rs-fMRI studies examining the impact of CHD have relied on predefined brain parcellations to compare group-level connectivity, limiting the ability to capture spatial alterations in neonatal brain networks in CHD. Understanding these network-level changes is critical for elucidating mechanisms of neurodevelopmental impairment and identifying early biomarkers of risk. To address these gaps, our study introduces two conceptual advances: 1) a data-driven approach to investigate atypical brain network development in high-risk CHD and 2) the use of a population-sized, independent dataset of healthy newborns to derive a normative set of neonatal brain networks. By analyzing a large rs-fMRI of human newborns (N=448; 219 females and 229 males), we identify atypical brain activity in the sensorimotor and limbic networks of newborns with complex CHD. Notably, before cardiovascular surgery, these networks are split into left and right hemispheric subnetworks. Postoperatively, these components coalesce into a singular, symmetric pattern resembling networks observed in healthy neonates. Our study highlights the potential of rs-fMRI to detect subtle, early functional disruptions in CHD and may inform future biomarkers of neurodevelopmental risk.

Significant Statement Congenital heart disease, the most common congenital disorder, affects 1% of live births and is associated with persistent neurodevelopmental impairments despite improved surgical survival. These deficits, including motor, socio-emotional, and cognitive challenges, may stem from early brain network disruptions. Prior resting-state fMRI studies in CHD relied on predefined parcellations, limiting detection of subtle spatial alterations. In this study, we used a data-driven approach and leveraged an independent normative dataset to define resting-state networks. Comparing CHD patients and healthy controls against these independently derived networks, we reveal atypical sensorimotor and limbic network organization preoperatively, which normalizes post-surgery. These findings highlight the potential of rs-fMRI to identify early biomarkers of neurodevelopmental risk and guide targeted interventions in this high-risk population.

Macrophage anti-bacterial activity is controlled by adenylate kinase 4–mediated mitochondrial DNA synthesis

New from Wei-Yao Chin, Shi-Chuen Miaw et al. (國立臺灣大學 National Taiwan University): macrophage Ak4 is vital for defense against bacteria. Ak4 fuels mtDNA synthesis ➡️ boosts mtROS production ➡️ kills pathogens. Loss of Ak4 leads to severe susceptibility.

Chin et al. discovered that macrophage-specific Ak4 regulates mtDNA synthesis, through which it controls mitochondrial biogenesis and mtROS levels and, sub.

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