Frank Paul Mora

Retired Haskell programmer. Was pro drummer & still play hours/day. Science, Philosophy, Literature. DMs blocked unless shared interests.

[오창명 @changmyung1981]

🧬🔥 Ferroptosis is emerging as a promising anticancer strategy—but why are potent ferroptosis inducers still struggling to become medicines?

A new review in Medicinal Chemistry Research examines small-molecule ferroptosis inducers and sensitizers across GPX4, SLC7A11/system xc⁻, FSP1, DHODH, and iron/lipid metabolism, highlighting the gap between cellular potency and clinical translation.

🔬 1. Multiple targets, distinct mechanisms

• GPX4 inhibition: Disrupts phospholipid peroxide detoxification.

• SLC7A11 inhibition: Restricts cystine uptake, depleting glutathione.

• FSP1 inhibition: Weakens GPX4-independent CoQ antioxidant defense.

• DHODH inhibition: Targets mitochondrial redox protection, although ferroptosis must be demonstrated separately.

• Iron-directed agents: Exploit lysosomal iron and lipid oxidation to trigger cancer-cell death.

⚡ 2. Promising compounds—but important limitations

GPX4-targeting compound (R)-7a:

• Cellular IC₅₀: 0.3 nM

• Selectivity index: 24,933

• Oral bioavailability: only 6.67%

Imidazole ketone erastin:

• Microsomal half-life improved from less than 5 minutes to 79 minutes.

• Achieved measurable tumor exposure.

• Dose-dependent weight loss remained a concern.

Erianin-derived hybrid compound 26:

• Cellular IC₅₀: 0.21–0.45 µM in NSCLC models.

• 61.43% tumor-growth inhibition in H1975 xenografts.

• Combines EGFR/tubulin-directed activity with ferroptosis-associated signaling changes.

These values arise from different experimental assays and should not be interpreted as direct comparisons of therapeutic efficacy.

🧬 3. The next opportunity: overcoming ferroptosis resistance

FSP1 and DHODH provide antioxidant defenses parallel to GPX4.

Importantly, KEAP1-mutant, NRF2-activated NSCLC may exhibit ferroptosis resistance involving FSP1.

This supports investigating biomarker-guided combination strategies rather than indiscriminately increasing oxidative stress.

💊 4. Medicinal chemistry matters as much as potency

The review emphasizes four requirements for successful drug development:

• Validated target engagement and selectivity

• Optimized electrophilic reactivity and molecular architecture

• Adequate pharmacokinetics and tumor exposure

• Demonstrated therapeutic windows and in vivo tolerability

A critical caveat: the direct GPX4-inhibitory mechanisms of classical probes RSL3 and ML162 have been challenged by evidence implicating TXNRD1.

🎯 The broader implication

The next breakthrough in ferroptosis therapeutics may not come from discovering a more potent inducer.

It may come from developing a selective, pharmacokinetically viable compound for a molecularly defined, ferroptosis-vulnerable tumor population.

No compound reviewed has yet achieved clinical validation specifically as a ferroptosis-directed anticancer therapy.

📄 Malik A, Naseer MA, Yadav M, et al.

Small-molecule ferroptosis inducers and sensitizers in anticancer drug discovery: medicinal chemistry, structure–activity relationships, and translational perspectives.

Medicinal Chemistry Research. 2026. Review article.

DOI: https://t.co/l2JnIb7qVi

#Ferroptosis #CancerMetabolism #GPX4 #FSP1 #SLC7A11 #DHODH #KEAP1 #NRF2 #NSCLC #MedicinalChemistry #DrugDiscovery #PrecisionOncology

Based on the uploaded 2026 review article, including its cross-target comparison (Table 8) and pharmacokinetic assessment (Table 9).

s00044-026-03632-4.pdf

[eLife - the journal @eLife]

Tau hyperphosphorylation impairs cooperative binding to microtubules and perturbs organelle trafficking in neurons
https://t.co/PHmaVS5JW2

[Frank Paul Mora @InTime_49]

@vineettiruvadi @AISafetyMemes People like Bill Gates throughing fuel on the fear fire not realizing that out-of-control AI can be unplugged.

[오창명 @changmyung1981]

🧬🔥 What if making adipocytes smaller actually increases adipose tissue inflammation and cell death?

A new study in Communications Biology reveals a surprising dual role for HDAC3 in adipose tissue plasticity: it restrains lipid accumulation while protecting visceral fat from excessive macrophage proliferation and apoptotic stress.

The central discovery: Adipocyte-specific HDAC3 deletion reduces visceral adipocyte hypertrophy but increases macrophage accumulation, crown-like structures, vascular remodeling, and cell-death susceptibility—without improving systemic insulin sensitivity.

🔬 1. HDAC3 regulates adipocyte expansion

Researchers studied adipocyte-specific Hdac3 knockout mice (H3fatKO) exposed to high-fat feeding for 4, 9, or 16 weeks.

Compared with controls, H3fatKO mice exhibited:

• Reduced epididymal white adipose tissue (eWAT) mass at earlier time points.

• Smaller visceral adipocytes after prolonged HFD exposure.

• Increased expression of lipid-metabolism genes, including Fasn, Acsl1, Acadl, and Pnpla2.

• No significant difference in total body-weight gain.

These findings support a role for HDAC3 in controlling adipocyte lipid turnover and expansion.

⚡ 2. Loss of HDAC3 promotes vascular remodeling

HDAC3-deficient visceral fat exhibited:

• Increased CD31⁺ vascular density.

• Elevated Vegfa and Pecam1 expression.

• Increased atypical multilocular adipocytes.

These changes are consistent with enhanced adipose tissue remodeling and previously reported browning-associated effects of HDAC3 deficiency.

However, greater vascularization did not translate into improved systemic metabolic outcomes.

🧬 3. Smaller adipocytes, more macrophages

Despite reduced adipocyte size, H3fatKO visceral fat accumulated more macrophages.

F4/80⁺ macrophages ↑

CD206⁺ macrophages ↑

Crown-like structures ↑

Multinucleated giant cells ↑

Interestingly, CD206⁺ macrophages remained abundant throughout high-fat feeding.

This challenges the simplistic interpretation that CD206 positivity necessarily indicates an anti-inflammatory, metabolically beneficial macrophage state.

🔥 4. Local macrophage proliferation contributes to remodeling

Immunofluorescence revealed increased colocalization of:

Ki-67⁺ / F4/80⁺

This supports increased local macrophage proliferation.

Meanwhile, circulating monocytes and splenic immune-cell populations showed limited genotype-dependent differences.

Co-culture experiments further demonstrated that HDAC3-silenced adipocytes increased macrophage CD11c and CD206 expression.

However, screening 119 cytokines and chemokines did not identify significant differences in the adipocyte secretome.

The responsible intercellular signals remain unresolved.

🧪 5. HDAC3 protects against apoptotic stress

In cultured adipocytes, HDAC3 silencing increased:

• Annexin V positivity.

• Casp3 and Bak1 expression.

• Cell-death susceptibility.

Meanwhile, Bcl2 expression decreased.

In vivo, visceral adipose tissue exhibited increased cleaved caspase-3 staining.

Importantly, cleaved caspase-3 colocalized with macrophage markers, suggesting that apoptotic signaling extends beyond adipocytes.

Thus, adipocyte HDAC3 deficiency creates a broader pro-apoptotic tissue microenvironment.

🧠 6. Why didn't metabolic health improve?

Despite reduced visceral adipocyte hypertrophy and enhanced tissue remodeling:

Glucose tolerance: No improvement

Insulin sensitivity: No improvement

Body-weight gain: No significant difference

These findings suggest that enhanced lipid turnover and smaller adipocytes are insufficient to improve systemic metabolism when accompanied by inflammatory remodeling and cell-death susceptibility.

🎯 7. Implications for obesity therapeutics

HDAC3 appears to function as a tissue-homeostatic regulator coordinating:

Lipid storage ↔ Adipocyte survival ↔ Macrophage turnover ↔ Vascular remodeling

Therapeutically, suppressing adipocyte HDAC3 may promote remodeling but could simultaneously compromise tissue integrity.

⚠️ Important limitations

The study examined male mice and cultured adipocytes.

The specific adipocyte-derived signals responsible for macrophage activation were not identified.

Increased resident macrophage proliferation was supported by Ki-67 staining, but altered recruitment or survival cannot be excluded.

The clinical consequences of HDAC3 modulation remain unknown.

The broader implication

Healthy adipose tissue remodeling requires more than reducing adipocyte size.

Metabolic flexibility must be balanced against cell survival, immune homeostasis, and tissue integrity.

HDAC3 may represent a molecular rheostat governing this balance during obesity.

📄 Coppi L, Severi I, Bonacina F, et al.

Hdac3 shapes adipocyte size, death susceptibility, macrophage turnover, and vascular remodeling in a mouse model of obesity.

Communications Biology. 2026. Article in Press.

DOI: https://t.co/okjBbeqU3t

#AdiposeTissue #HDAC3 #Obesity #AdiposePlasticity #Macrophages #Immunometabolism #Epigenetics #AdipocyteDeath #InsulinResistance #MetabolicHealth #VascularRemodeling #Geroscience

[Felix Scholkmann @FScholkmann]

A new hypothesis about #fibromyalgia:
Gabbai & Carmi, 2026, https://t.co/cbyHpMHatv
Impaired upstream regulation → redistribution of flow toward non-nutritive pathways → reduced capillary perfusion → intermittent tissue hypoxia → nociceptor sensitization → pain & tenderness

[Catalina Vasilescu, PhD @_CVasilescu]

Happy Sunday with a delicious, fresh edition of Mitochondria in Health and Disease!
Full edition online: https://t.co/Ta0nzmPhJe

Selected highlights below! Always thankful for @gavinmcstay2, @mitoscientist, @mitoworld_org, and all mitofriends!

[Frank Paul Mora @InTime_49]

@vineettiruvadi @AndrewCurran_ Consciousness and feeling are biological and CS nor AI has nothing comparable.

[Waggoner Lab @LabWaggoner]

NAD+ metabolic restoration resolves the inflammation-immunocompetence trade-off in lung graft-versus-host disease
https://t.co/IfTk19Llof
@ScienceAdvances 🇨🇳

[Frank Paul Mora @InTime_49]

@vineettiruvadi Medical diagnosis is an analytic process. Prognosis is according to a model. Analysis and models are integral in math and coding.

[Frank Paul Mora @InTime_49]

@erenturkmen Movies are not evidence.

[@BioAI_Neuro @BioAI_NeuralNet]

Cognitive computational neuroscience
https://t.co/36JzFigmF8

1/ Move beyond brain mapping.
Mapping which brain regions activate during a task is not enough to explain cognition. We need computational models that reproduce behavior and explain how neural activity generates perception, learning, decision-making, and action. The goal is to understand the mechanism, not just the location.

2/ Build models that perform cognitive tasks.
Allen Newell argued that understanding cognition requires constructing systems that actually perform the functions we want to explain. A theory of decision-making, for example, should predict choices under different conditions—not merely describe them verbally. Simulations help test whether proposed mechanisms work together to produce intelligent behavior.

3/ Integrate three disciplines.
Cognitive science explains the computations underlying thought; computational neuroscience investigates how neural circuits implement those computations; AI develops algorithms that perform complex tasks. Each provides different constraints. Combining them could produce models that are simultaneously behaviorally effective, computationally explicit, and biologically grounded.

4/ Neural networks are a bridge between brains and AI.
Deep neural networks learn hierarchical representations that can resemble those observed in biological sensory systems. Research has shown that networks trained for object recognition can predict aspects of visual cortical representations. However, predictive similarity does not prove that the brain uses the same algorithms. Models must also be tested against neural and behavioral evidence.

5/ Biological neurons offer more than artificial units.
Most conventional artificial neural networks use simplified units that combine inputs and apply nonlinear transformations. Biological neurons exhibit action potentials, dendritic computations, recurrent signaling, oscillations, and complex temporal dynamics. Incorporating these features into task-performing models may reveal computational principles that simpler AI architectures overlook.

6/ Neural decoding is not a complete explanation.
Decoding asks what information can be extracted from neural activity. Encoding models predict neural responses; representational similarity analysis compares patterns of activity; connectivity models examine interactions. These methods constrain theories, but they do not necessarily explain how the brain transforms information to solve a task. Mechanistic models must connect representations to computation and behavior.

7/ Bayesian inference offers a theory of perception and reasoning.
The brain must interpret noisy sensory information using prior knowledge about the world. Bayesian models formalize this process by combining prior beliefs with incoming evidence. Generative models go further by representing how hidden causes produce observations. They offer a framework for studying uncertainty, causal reasoning, concept formation, and the ability to learn from limited experience.
8/ Learning and control require multiple strategies.
Reinforcement learning provides a framework for understanding how actions and feedback shape future behavior. Model-free approaches learn values or policies from experience; model-based approaches use an internal model to evaluate possible outcomes; episodic approaches reuse specific past experiences. Understanding how biological brains combine these strategies could inform more adaptive AI systems.

9/ Combine bottom-up and top-down approaches.
Bottom-up neuroscience begins with neurons, circuits, and measured activity. Top-down approaches begin with a cognitive function and ask what computations are required to perform it. Neither is sufficient alone. Strong theories should explain how biological mechanisms support meaningful behavior—and use behavioral requirements to identify which neural mechanisms matter.

10/ The future is an integrated NeuroAI.
A major challenge is to connect three levels: computational goals, representations and algorithms, and neurobiological implementation. This requires collaboration across neuroscience, cognitive science, mathematics, and AI, along with shared datasets, models, tasks, and evaluation methods. The ultimate ambition is to build systems that perform intelligent tasks while explaining how brains learn, represent knowledge, and adapt.

The big idea:
The next leap in AI and neuroscience may come from treating the brain not simply as a source of data, but as a system whose computational principles can be tested through models that connect neural mechanisms to intelligent behavior.

[Dr. Patrick Hwu @PatrickHwuMD]

🧬 #ScienceSaturday What if the same CAR could behave differently depending on the type of T cell carrying it?

CAR-T therapies are most often engineered using alpha beta (αβ) T cells, but another population, gamma delta (γδ) T cells, is gaining interest for its potential in #cancer immunotherapy.

🔬 In a new study from our team @MoffittNews, we compared αβ and γδ T cells engineered with the same CAR. While both could kill cancer cells, the CAR triggered surprisingly different signaling and metabolic programs depending on the T-cell type.

γδ CAR-T cells showed lower glycolytic and mitochondrial activity and weaker activation of AP-1, an important pathway involved in T-cell function. The team also identified TXNIP as a potential metabolic target: inhibiting it improved several measures of γδ T-cell #metabolic fitness and function.

🛡️ We then designed a new synthetic costimulatory receptor to strengthen signaling in γδ CAR-T cells, which improved their persistence in preclinical models.

💡 Why does this matter? #CAR engineering may not be one-size-fits-all. Understanding the unique #biology of different T-cell populations could help us design cell therapies that are better matched to the cells carrying them, and ultimately improve their function and persistence.

There’s still more work to do, but this study highlights an important opportunity: instead of adapting #CARs built for one type of T cell, we may be able to #engineer them around the unique strengths of each.

I'm especially proud of Dr. Daniel Abate-Daga, first author Xiomar E. Bustos and the entire team behind this exciting research!

And we're already looking toward the next step: We plan to bring this new costimulatory receptor into the clinic for patients with metastatic prostate #cancer by spring 2027. @Nature @NatImmunol @NatureMedicine @NaturePortfolio @NatureBiotech

Read the study: https://t.co/z1kJMbwStE

[Paul Bays @BaysLab]

Our review of Bayesian efficient coding as a theory of perception is out now in TICS – with Ivan Tomić and Máté Lengyel. https://t.co/mEpyKjjvfv

[오창명 @changmyung1981]

🧬⚡ What if we could treat diabetes and obesity by electrically removing excess glucose—without insulin or glucose-lowering drugs?

A groundbreaking study in Science introduces ECHO (Electrocatalytic Closed-Loop Health Optimization), a wirelessly powered implant that converts circulating glucose into gluconate, enabling glucose control while promoting fat utilization.

The central discovery: An implantable electrocatalyst can directly regulate glucose availability and shift systemic energy metabolism without administering drugs.

🔬 1. Engineering an implantable glucose-removal system

Researchers developed a catalyst consisting of platinum-decorated gold nanoclusters embedded in porous graphite felt (GF_Au@Pt).

When electrically activated, the device catalyzes:

Glucose → Gluconate → Predominantly renal clearance

The system operates at:

• 0.75 V

• 10 mA

• Wireless power transmission at 13.56 MHz

Unlike conventional insulin therapy, which promotes glucose uptake and utilization, ECHO directly converts glucose into a metabolite that is largely excreted.

⚡ 2. Rapid glucose normalization in diabetic mice

In obese diabetic db/db mice, wireless ECHO activation restored elevated blood glucose to the normal range within approximately 60–90 minutes.

Repeated daily stimulation maintained glycemic control for six weeks.

Importantly, no detectable hypoglycemia occurred under the tested conditions.

🧬 3. Glucose removal promotes fat utilization

After six weeks of treatment, ECHO-treated mice exhibited:

• Up to 10% body-weight reduction

• Lower circulating triglycerides

• Reduced insulin concentrations

• Increased circulating free fatty acids

• Increased β-hydroxybutyrate and acetoacetate

Food intake remained unchanged.

These results are consistent with a shift toward fat mobilization and ketone production.

The proposed metabolic sequence is:

Glucose oxidation → Reduced available metabolic energy → Increased lipid mobilization → Ketogenesis → Body-weight reduction

🔥 4. Autonomous closed-loop glucose control

The researchers integrated ECHO with a commercial continuous glucose monitor (CGM) and smartphone-controlled wireless activation.

The system:

• Continuously monitored glucose.

• Activated electrocatalysis when glucose exceeded a preset threshold.

• Automatically stopped stimulation as glucose normalized.

• Maintained glucose control over the CGM's 12-day operational lifespan.

This demonstrates a feedback-controlled therapeutic approach without insulin delivery.

🧪 5. Preliminary biocompatibility and stability

The implant maintained catalytic function during prolonged use.

Investigators reported no detectable systemic gold or platinum accumulation, substantial inflammatory response, or glucose-lowering-associated behavioral abnormalities under the tested conditions.

Blood pH remained stable, despite increased ketone production.

🎯 6. Implications for metabolic therapeutics

ECHO introduces a fundamentally different treatment concept:

Instead of pharmacologically modifying metabolic signaling, directly regulate the concentration of a circulating metabolic substrate.

Potential future applications include:

• Drug-sparing glucose management

• Closed-loop metabolic implants

• Electrically adjustable substrate clearance

• Bioelectronic approaches to obesity-associated diabetes

⚠️ Important limitations

This remains a preclinical proof of concept, primarily evaluated in db/db mice.

Human efficacy and long-term implant safety have not been established.

The physiological consequences of sustained glucose removal, altered substrate partitioning, and increased ketogenesis require further investigation.

Additionally, reductions in circulating glucose and body weight do not independently establish long-term improvements in metabolic health.

The broader implication

This study extends bioelectronic medicine beyond electrical stimulation of nerves and tissues.

Metabolism itself can potentially become an electronically controllable therapeutic target.

The next generation of metabolic devices may combine continuous sensing, catalytic chemistry, and programmable feedback to regulate circulating metabolites directly.

📄 Maity D, Guha Ray P, Buchmann P, Charpin-El Hamri G, Fussenegger M.

Wireless electrocatalytic closed-loop system for drug-free management of diabesity.

Science. 2026;394(6822). Published October 22, 2026.

DOI: https://t.co/1oiuC44F0B

#BioelectronicMedicine #Diabetes #Obesity #Diabesity #Electrocatalysis #GlucoseMetabolism #MetabolicEngineering #ContinuousGlucoseMonitoring #ClosedLoopSystems #FatOxidation #Ketogenesis #PrecisionMedicine #MetabolicHealth

[Dr. Jay Wrigley @hormonedietdoc]

I see far too many women who have been prescribed thyroid medication, only to find that their symptoms barely improve, even though their lab numbers look better.

Two things I frequently find:

Thyroid function doesn’t operate in isolation. Other hormonal, metabolic, and physiological factors may also need attention.
The medication itself may not be the best fit, or the dose may need adjustment.

Getting thyroid numbers into range is not the same thing as restoring someone’s health.

The goal is to improve how you feel and function, not just how your labs look.

[Vera Kober Art @vera_kober_art]

My flower painting of a chrysanthemum 🖌️

[Vineet @vineettiruvadi]

At the very least, might help get some better intuitions for the concept of a phase space

[Vineet @vineettiruvadi]

Updated my ECGTensor repository with some cool visuals: https://t.co/jvcA5r2xM3

[Frank Paul Mora @InTime_49]

@vineettiruvadi Concepts are abstract/concrete, simple/complex, general/specific

[Waggoner Lab @LabWaggoner]

IFN-λ signaling to maternal dendritic cells protects against congenital Zika virus infection
https://t.co/5GkAySVpny
@ScienceAdvances @LazearLab @MargaretDedloff @UNC